diff --git a/fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/ExpressionOptimization.java b/fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/ExpressionOptimization.java
index 1852994b7af120..abf57057601dc8 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/ExpressionOptimization.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/ExpressionOptimization.java
@@ -41,20 +41,19 @@
 public class ExpressionOptimization extends ExpressionRewrite {
     public static final List<ExpressionRewriteRule> OPTIMIZE_REWRITE_RULES = ImmutableList.of(
             bottomUp(
-                    ExtractCommonFactorRule.INSTANCE,
-                    DistinctPredicatesRule.INSTANCE,
-                    SimplifyComparisonPredicate.INSTANCE,
-                    SimplifyInPredicate.INSTANCE,
-                    SimplifyDecimalV3Comparison.INSTANCE,
-                    SimplifyRange.INSTANCE,
-                    OrToIn.INSTANCE,
-                    SimplifyRange.INSTANCE,
-                    DateFunctionRewrite.INSTANCE,
-                    ArrayContainToArrayOverlap.INSTANCE,
-                    CaseWhenToIf.INSTANCE,
-                    TopnToMax.INSTANCE,
-                    NullSafeEqualToEqual.INSTANCE,
-                    LikeToEqualRewrite.INSTANCE
+                ExtractCommonFactorRule.INSTANCE,
+                DistinctPredicatesRule.INSTANCE,
+                SimplifyComparisonPredicate.INSTANCE,
+                SimplifyInPredicate.INSTANCE,
+                SimplifyDecimalV3Comparison.INSTANCE,
+                OrToIn.INSTANCE,
+                SimplifyRange.INSTANCE,
+                DateFunctionRewrite.INSTANCE,
+                ArrayContainToArrayOverlap.INSTANCE,
+                CaseWhenToIf.INSTANCE,
+                TopnToMax.INSTANCE,
+                NullSafeEqualToEqual.INSTANCE,
+                LikeToEqualRewrite.INSTANCE
             )
     );
     private static final ExpressionRuleExecutor EXECUTOR = new ExpressionRuleExecutor(OPTIMIZE_REWRITE_RULES);
diff --git a/fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/rules/OrToIn.java b/fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/rules/OrToIn.java
index ec51c8f5367a78..83da8055037242 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/rules/OrToIn.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/nereids/rules/expression/rules/OrToIn.java
@@ -17,37 +17,44 @@
 
 package org.apache.doris.nereids.rules.expression.rules;
 
-import org.apache.doris.common.Pair;
 import org.apache.doris.nereids.rules.expression.ExpressionBottomUpRewriter;
 import org.apache.doris.nereids.rules.expression.ExpressionPatternMatcher;
 import org.apache.doris.nereids.rules.expression.ExpressionPatternRuleFactory;
 import org.apache.doris.nereids.rules.expression.ExpressionRewrite;
 import org.apache.doris.nereids.rules.expression.ExpressionRewriteContext;
-import org.apache.doris.nereids.trees.expressions.And;
-import org.apache.doris.nereids.trees.expressions.CompoundPredicate;
 import org.apache.doris.nereids.trees.expressions.EqualTo;
 import org.apache.doris.nereids.trees.expressions.Expression;
 import org.apache.doris.nereids.trees.expressions.InPredicate;
+import org.apache.doris.nereids.trees.expressions.NamedExpression;
 import org.apache.doris.nereids.trees.expressions.Or;
-import org.apache.doris.nereids.trees.expressions.Slot;
 import org.apache.doris.nereids.trees.expressions.literal.Literal;
 import org.apache.doris.nereids.util.ExpressionUtils;
-import org.apache.doris.nereids.util.MutableState;
 
 import com.google.common.collect.ImmutableList;
-import com.google.common.collect.Lists;
-import com.google.common.collect.Sets;
+import com.google.common.collect.Maps;
 
 import java.util.ArrayList;
-import java.util.LinkedHashMap;
 import java.util.LinkedHashSet;
 import java.util.List;
 import java.util.Map;
 import java.util.Set;
 
 /**
- * dependends on SimplifyRange rule
- *
+ * Used to convert multi equalTo which has same slot and compare to a literal of disjunction to a InPredicate so that
+ * it could be push down to storage engine.
+ * example:
+ * col1 = 1 or col1 = 2 or col1 = 3 and (col2 = 4)
+ * col1 = 1 and col1 = 3 and col2 = 3 or col2 = 4
+ * (col1 = 1 or col1 = 2) and  (col2 = 3 or col2 = 4)
+ * <p>
+ * would be converted to:
+ * col1 in (1, 2) or col1 = 3 and (col2 = 4)
+ * col1 = 1 and col1 = 3 and col2 = 3 or col2 = 4
+ * (col1 in (1, 2) and (col2 in (3, 4)))
+ * The generic type declaration and the overridden 'rewrite' function in this class may appear unconventional
+ * because we need to maintain a map passed between methods in this class. But the owner of this module prohibits
+ * adding any additional rule-specific fields to the default ExpressionRewriteContext. However, the entire expression
+ * rewrite framework always passes an ExpressionRewriteContext of type context to all rules.
  */
 public class OrToIn implements ExpressionPatternRuleFactory {
 
@@ -58,255 +65,82 @@ public class OrToIn implements ExpressionPatternRuleFactory {
     @Override
     public List<ExpressionPatternMatcher<? extends Expression>> buildRules() {
         return ImmutableList.of(
-                matchesTopType(Or.class).then(OrToIn.INSTANCE::rewrite)
+                matchesTopType(Or.class).then(OrToIn::rewrite)
         );
     }
 
     public Expression rewriteTree(Expression expr, ExpressionRewriteContext context) {
-        if (expr instanceof CompoundPredicate) {
-            expr = SimplifyRange.rewrite((CompoundPredicate) expr);
-        }
         ExpressionBottomUpRewriter bottomUpRewriter = ExpressionRewrite.bottomUp(this);
         return bottomUpRewriter.rewrite(expr, context);
     }
 
-    private Expression rewrite(Or or) {
-        if (or.getMutableState(MutableState.KEY_OR_TO_IN).isPresent()) {
-            return or;
-        }
-        Pair<Expression, Expression> pair = extractCommonConjunct(or);
-        Expression result = tryToRewriteIn(pair.second);
-        if (pair.first != null) {
-            result = new And(pair.first, result);
-        }
-        result.setMutableState(MutableState.KEY_OR_TO_IN, 1);
-        return result;
-    }
-
-    private Expression tryToRewriteIn(Expression or) {
-        or.setMutableState(MutableState.KEY_OR_TO_IN, 1);
-        List<Expression> disjuncts = ExpressionUtils.extractDisjunction(or);
-        for (Expression disjunct : disjuncts) {
-            if (!hasInOrEqualChildren(disjunct)) {
-                return or;
+    private static Expression rewrite(Or or) {
+        // NOTICE: use linked hash map to avoid unstable order or entry.
+        //  unstable order entry lead to dead loop since return expression always un-equals to original one.
+        Map<NamedExpression, Set<Literal>> slotNameToLiteral = Maps.newLinkedHashMap();
+        Map<Expression, NamedExpression> disConjunctToSlot = Maps.newLinkedHashMap();
+        List<Expression> expressions = ExpressionUtils.extractDisjunction(or);
+        for (Expression expression : expressions) {
+            if (expression instanceof EqualTo) {
+                handleEqualTo((EqualTo) expression, slotNameToLiteral, disConjunctToSlot);
+            } else if (expression instanceof InPredicate) {
+                handleInPredicate((InPredicate) expression, slotNameToLiteral, disConjunctToSlot);
             }
         }
-
-        Map<Expression, Set<Literal>> candidates = getCandidates(disjuncts.get(0));
-        if (candidates.isEmpty()) {
+        if (disConjunctToSlot.isEmpty()) {
             return or;
         }
 
-        // verify each candidate
-        for (int i = 1; i < disjuncts.size(); i++) {
-            Map<Expression, Set<Literal>> otherCandidates = getCandidates(disjuncts.get(i));
-            if (otherCandidates.isEmpty()) {
-                return or;
-            }
-            candidates = mergeCandidates(candidates, otherCandidates);
-            if (candidates.isEmpty()) {
-                return or;
+        List<Expression> rewrittenOr = new ArrayList<>();
+        for (Map.Entry<NamedExpression, Set<Literal>> entry : slotNameToLiteral.entrySet()) {
+            Set<Literal> literals = entry.getValue();
+            if (literals.size() >= REWRITE_OR_TO_IN_PREDICATE_THRESHOLD) {
+                InPredicate inPredicate = new InPredicate(entry.getKey(), ImmutableList.copyOf(entry.getValue()));
+                rewrittenOr.add(inPredicate);
             }
         }
-        if (!candidates.isEmpty()) {
-            Expression conjunct = candidatesToFinalResult(candidates);
-            boolean keep = keepOriginalOrExpression(disjuncts);
-            if (keep) {
-                return new And(conjunct, or);
+        for (Expression expression : expressions) {
+            if (disConjunctToSlot.get(expression) == null) {
+                rewrittenOr.add(expression);
             } else {
-                return conjunct;
-            }
-        }
-        return or;
-    }
-
-    private boolean keepOriginalOrExpression(List<Expression> disjuncts) {
-        for (Expression disjunct : disjuncts) {
-            List<Expression> conjuncts = ExpressionUtils.extractConjunction(disjunct);
-            if (conjuncts.size() > 1) {
-                return true;
-            }
-        }
-        return false;
-    }
-
-    private boolean containsAny(Set a, Set b) {
-        for (Object x : a) {
-            if (b.contains(x)) {
-                return true;
-            }
-        }
-        return false;
-    }
-
-    private Map<Expression, Set<Literal>> mergeCandidates(
-            Map<Expression, Set<Literal>> a,
-            Map<Expression, Set<Literal>> b) {
-        Map<Expression, Set<Literal>> result = new LinkedHashMap<>();
-        for (Expression expr : a.keySet()) {
-            Set<Literal> otherLiterals = b.get(expr);
-            if (otherLiterals != null) {
-                Set<Literal> literals = a.get(expr);
-                literals.addAll(otherLiterals);
-                if (!literals.isEmpty()) {
-                    result.put(expr, literals);
-                }
-            }
-        }
-        return result;
-    }
-
-    private Expression candidatesToFinalResult(Map<Expression, Set<Literal>> candidates) {
-        List<Expression> conjuncts = new ArrayList<>();
-        for (Expression key : candidates.keySet()) {
-            Set<Literal> literals = candidates.get(key);
-            if (literals.size() < REWRITE_OR_TO_IN_PREDICATE_THRESHOLD) {
-                for (Literal literal : literals) {
-                    conjuncts.add(new EqualTo(key, literal));
+                Set<Literal> literals = slotNameToLiteral.get(disConjunctToSlot.get(expression));
+                if (literals.size() < REWRITE_OR_TO_IN_PREDICATE_THRESHOLD) {
+                    rewrittenOr.add(expression);
                 }
-            } else {
-                conjuncts.add(new InPredicate(key, ImmutableList.copyOf(literals)));
             }
         }
-        return ExpressionUtils.and(conjuncts);
-    }
 
-    /*
-       it is not necessary to rewrite "a like 'xyz' or a=1 or a=2" to "a like 'xyz' or a in (1, 2)",
-       because we cannot push "a in (1, 2)" into storage layer
-     */
-    private boolean hasInOrEqualChildren(Expression disjunct) {
-        List<Expression> conjuncts = ExpressionUtils.extractConjunction(disjunct);
-        for (Expression conjunct : conjuncts) {
-            if (conjunct instanceof EqualTo || conjunct instanceof InPredicate) {
-                return true;
-            }
-        }
-        return false;
+        return ExpressionUtils.or(rewrittenOr);
     }
 
-    // conjuncts.get(idx) has different input slots
-    private boolean independentConjunct(int idx, List<Expression> conjuncts) {
-        Expression conjunct = conjuncts.get(idx);
-        Set<Slot> targetSlots = conjunct.getInputSlots();
-        if (conjuncts.size() == 1) {
-            return true;
+    private static void handleEqualTo(EqualTo equal, Map<NamedExpression, Set<Literal>> slotNameToLiteral,
+                               Map<Expression, NamedExpression> disConjunctToSlot) {
+        Expression left = equal.left();
+        Expression right = equal.right();
+        if (left instanceof NamedExpression && right instanceof Literal) {
+            addSlotToLiteral((NamedExpression) left, (Literal) right, slotNameToLiteral);
+            disConjunctToSlot.put(equal, (NamedExpression) left);
+        } else if (right instanceof NamedExpression && left instanceof Literal) {
+            addSlotToLiteral((NamedExpression) right, (Literal) left, slotNameToLiteral);
+            disConjunctToSlot.put(equal, (NamedExpression) right);
         }
-        for (int i = 0; i < conjuncts.size(); i++) {
-            if (i != idx) {
-                Set<Slot> otherInput = Sets.newHashSet();
-                otherInput.addAll(conjuncts.get(i).getInputSlots());
-                otherInput.retainAll(targetSlots);
-                if (!otherInput.isEmpty()) {
-                    return false;
-                }
-            }
-        }
-        return true;
     }
 
-    private Map<Expression, Set<Literal>> getCandidates(Expression disjunct) {
-        List<Expression> conjuncts = ExpressionUtils.extractConjunction(disjunct);
-        Map<Expression, Set<Literal>> candidates = new LinkedHashMap<>();
-        // collect candidates from the first disjunction
-        for (int idx = 0; idx < conjuncts.size(); idx++) {
-            if (!independentConjunct(idx, conjuncts)) {
-                continue;
-            }
-            // find pattern: A=1 / A in (1, 2, 3 ...)
-            // candidates: A->[1] / A -> [1, 2, 3, ...]
-            Expression conjunct = conjuncts.get(idx);
-            Expression compareExpr = null;
-            if (conjunct instanceof EqualTo) {
-                EqualTo eq = (EqualTo) conjunct;
-                Literal literal = null;
-                if (!(eq.left() instanceof Literal) && eq.right() instanceof Literal) {
-                    compareExpr = eq.left();
-                    literal = (Literal) eq.right();
-                } else if (!(eq.right() instanceof Literal) && eq.left() instanceof Literal) {
-                    compareExpr = eq.right();
-                    literal = (Literal) eq.left();
-                }
-                if (compareExpr != null) {
-                    Set<Literal> literals = candidates.get(compareExpr);
-                    if (literals == null) {
-                        literals = Sets.newHashSet();
-                        literals.add(literal);
-                        candidates.put(compareExpr, literals);
-                    } else {
-                        // pattern like (A=1 and A=2) should be processed by SimplifyRange rule
-                        // OrToIn rule does apply to this expression
-                        candidates.clear();
-                        break;
-
-                    }
-                }
-            } else if (conjunct instanceof InPredicate) {
-                InPredicate inPredicate = (InPredicate) conjunct;
-                Set<Literal> literalOptions = new LinkedHashSet<>();
-                boolean allLiteralOpts = true;
-                for (Expression opt : inPredicate.getOptions()) {
-                    if (opt instanceof Literal) {
-                        literalOptions.add((Literal) opt);
-                    } else {
-                        allLiteralOpts = false;
-                        break;
-                    }
-                }
-
-                if (allLiteralOpts) {
-                    Set<Literal> alreadyMappedLiterals = candidates.get(inPredicate.getCompareExpr());
-                    if (alreadyMappedLiterals == null) {
-                        candidates.put(inPredicate.getCompareExpr(), literalOptions);
-                    } else {
-                        // pattern like (A=1 and A in (1, 2)) should be processed by SimplifyRange rule
-                        // OrToIn rule does apply to this expression
-                        candidates.clear();
-                        break;
-                    }
-                }
+    private static void handleInPredicate(InPredicate inPredicate, Map<NamedExpression, Set<Literal>> slotNameToLiteral,
+                                   Map<Expression, NamedExpression> disConjunctToSlot) {
+        // TODO a+b in (1,2,3...) is not supported now
+        if (inPredicate.getCompareExpr() instanceof NamedExpression
+                && inPredicate.getOptions().stream().allMatch(opt -> opt instanceof Literal)) {
+            for (Expression opt : inPredicate.getOptions()) {
+                addSlotToLiteral((NamedExpression) inPredicate.getCompareExpr(), (Literal) opt, slotNameToLiteral);
             }
+            disConjunctToSlot.put(inPredicate, (NamedExpression) inPredicate.getCompareExpr());
         }
-        return candidates;
     }
 
-    /**
-     * (a and b and ...) or (a and c and ...)
-     * =>
-     * a and [(b and ...) or (c and ...)]
-     * extract the common part: a
-     * and remaining part (b and ...) or (c and ...)
-     * @returns Pair (common, remaining)
-     */
-    private Pair<Expression, Expression> extractCommonConjunct(Or or) {
-        List<Expression> disjuncts = ExpressionUtils.extractDisjunction(or);
-        List<List<Expression>> conjunctsList = Lists.newArrayList();
-        for (Expression disjunct : disjuncts) {
-            conjunctsList.add(ExpressionUtils.extractConjunction(disjunct));
-        }
-        List<Expression> commons = Lists.newArrayList();
-        for (Expression a : conjunctsList.get(0)) {
-            boolean isCommon = true;
-            for (int i = 1; i < disjuncts.size(); i++) {
-                if (!conjunctsList.get(i).contains(a)) {
-                    isCommon = false;
-                    break;
-                }
-            }
-            if (isCommon) {
-                commons.add(a);
-            }
-        }
-        if (!commons.isEmpty()) {
-            List<Expression> remainPart = Lists.newArrayList();
-            for (int i = 0; i < disjuncts.size(); i++) {
-                conjunctsList.get(i).removeAll(commons);
-                remainPart.add(ExpressionUtils.and(conjunctsList.get(i)));
-            }
-            Expression remainOr = ExpressionUtils.or(remainPart);
-            return Pair.of(ExpressionUtils.and(commons), remainOr);
-        } else {
-            return Pair.of(null, or);
-        }
+    private static void addSlotToLiteral(NamedExpression namedExpression, Literal literal,
+            Map<NamedExpression, Set<Literal>> slotNameToLiteral) {
+        Set<Literal> literals = slotNameToLiteral.computeIfAbsent(namedExpression, k -> new LinkedHashSet<>());
+        literals.add(literal);
     }
 }
diff --git a/fe/fe-core/src/main/java/org/apache/doris/nereids/util/MutableState.java b/fe/fe-core/src/main/java/org/apache/doris/nereids/util/MutableState.java
index 528c19576bb40e..cdd0896e0c8809 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/nereids/util/MutableState.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/nereids/util/MutableState.java
@@ -28,9 +28,6 @@ public interface MutableState {
     String KEY_PARENT = "parent";
     String KEY_RF_JUMP = "rf-jump";
     String KEY_PUSH_TOPN_TO_AGG = "pushTopnToAgg";
-
-    String KEY_OR_TO_IN = "or_to_in";
-
     <T> Optional<T> get(String key);
 
     MutableState set(String key, Object value);
diff --git a/fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/OrToInTest.java b/fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/OrToInTest.java
index f5615d59fe8181..98eac158185c5a 100644
--- a/fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/OrToInTest.java
+++ b/fe/fe-core/src/test/java/org/apache/doris/nereids/rules/rewrite/OrToInTest.java
@@ -19,6 +19,7 @@
 
 import org.apache.doris.nereids.rules.expression.ExpressionRewriteTestHelper;
 import org.apache.doris.nereids.rules.expression.rules.OrToIn;
+import org.apache.doris.nereids.trees.expressions.And;
 import org.apache.doris.nereids.trees.expressions.Expression;
 import org.apache.doris.nereids.trees.expressions.InPredicate;
 import org.apache.doris.nereids.trees.expressions.NamedExpression;
@@ -38,8 +39,22 @@ void test1() {
         String expr = "col1 = 1 or col1 = 2 or col1 = 3 and (col2 = 4)";
         Expression expression = PARSER.parseExpression(expr);
         Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("(col1 IN (1, 2, 3) AND (col1 IN (1, 2) OR ((col1 = 3) AND (col2 = 4))))",
-                rewritten.toSql());
+        Set<InPredicate> inPredicates = rewritten.collect(e -> e instanceof InPredicate);
+        Assertions.assertEquals(1, inPredicates.size());
+        InPredicate inPredicate = inPredicates.iterator().next();
+        NamedExpression namedExpression = (NamedExpression) inPredicate.getCompareExpr();
+        Assertions.assertEquals("col1", namedExpression.getName());
+        List<Expression> options = inPredicate.getOptions();
+        Assertions.assertEquals(2, options.size());
+        Set<Integer> opVals = ImmutableSet.of(1, 2);
+        for (Expression op : options) {
+            Literal literal = (Literal) op;
+            Assertions.assertTrue(opVals.contains(((Byte) literal.getValue()).intValue()));
+        }
+        Set<And> ands = rewritten.collect(e -> e instanceof And);
+        Assertions.assertEquals(1, ands.size());
+        And and = ands.iterator().next();
+        Assertions.assertEquals("((col1 = 3) AND (col2 = 4))", and.toSql());
     }
 
     @Test
@@ -47,7 +62,7 @@ void test2() {
         String expr = "col1 = 1 and col1 = 3 and col2 = 3 or col2 = 4";
         Expression expression = PARSER.parseExpression(expr);
         Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("(col2 = 4)",
+        Assertions.assertEquals("((((col1 = 1) AND (col1 = 3)) AND (col2 = 3)) OR (col2 = 4))",
                 rewritten.toSql());
     }
 
@@ -89,7 +104,7 @@ void test5() {
         String expr = "col = 1 or (col = 2 and (col = 3 or col = 4 or col = 5))";
         Expression expression = PARSER.parseExpression(expr);
         Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("(col = 1)",
+        Assertions.assertEquals("((col = 1) OR ((col = 2) AND col IN (3, 4, 5)))",
                 rewritten.toSql());
     }
 
@@ -106,7 +121,7 @@ void test7() {
         String expr = "A = 1 or A = 2 or abs(A)=5 or A in (1, 2, 3) or B = 1 or B = 2 or B in (1, 2, 3) or B+1 in (4, 5, 7)";
         Expression expression = PARSER.parseExpression(expr);
         Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("(((A IN (1, 2, 3) OR (abs(A) = 5)) OR B IN (1, 2, 3)) OR (B + 1) IN (4, 5, 7))", rewritten.toSql());
+        Assertions.assertEquals("(((A IN (1, 2, 3) OR B IN (1, 2, 3)) OR (abs(A) = 5)) OR (B + 1) IN (4, 5, 7))", rewritten.toSql());
     }
 
     @Test
@@ -127,82 +142,4 @@ void testEnsureOrder() {
         Assertions.assertEquals("(col1 IN (1, 2) OR col2 IN (1, 2))",
                 rewritten.toSql());
     }
-
-    @Test
-    void test9() {
-        String expr = "col1=1 and (col2=1 or col2=2)";
-        Expression expression = PARSER.parseExpression(expr);
-        Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("((col1 = 1) AND col2 IN (1, 2))",
-                rewritten.toSql());
-    }
-
-    @Test
-    void test10() {
-        // recursive rewrites
-        String expr = "col1=1 or (col2 = 2 and (col3=4 or col3=5))";
-        Expression expression = PARSER.parseExpression(expr);
-        Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("((col1 = 1) OR ((col2 = 2) AND col3 IN (4, 5)))",
-                rewritten.toSql());
-    }
-
-    @Test
-    void test11() {
-        // rewrite multi-inPredicates
-        String expr = "(a=1 and b=2 and c=3) or (a=2 and b=2 and c=4)";
-        Expression expression = PARSER.parseExpression(expr);
-        Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("((b = 2) AND ((a IN (1, 2) AND c IN (3, 4)) AND (((a = 1) AND (c = 3)) OR ((a = 2) AND (c = 4)))))",
-                rewritten.toSql());
-    }
-
-    @Test
-    void test12() {
-        // no rewrite
-        String expr = "a in (1, 2) and a in (3, 4)";
-        Expression expression = PARSER.parseExpression(expr);
-        Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("FALSE",
-                rewritten.toSql());
-    }
-
-    @Test
-    void test13() {
-        // no rewrite, because of "a like 'xyz'"
-        String expr = "a like 'xyz% or a=1 or a=2': no extract";
-        Expression expression = PARSER.parseExpression(expr);
-        Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("(a like 'xyz% or a=1 or a=2')",
-                rewritten.toSql());
-    }
-
-    @Test
-    void test14() {
-        // no rewrite, because of "f(a)"
-        String expr = "(a=1 and f(a)=2) or a=3";
-        Expression expression = PARSER.parseExpression(expr);
-        Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("(((a = 1) AND (f(a) = 2)) OR (a = 3))",
-                rewritten.toSql());
-    }
-
-    @Test
-    void test15() {
-        // no rewrite, because of "a like 'xyz'"
-        String expr = "x=1 or (a=1 and b=2) or (a=2 and c=3)";
-        Expression expression = PARSER.parseExpression(expr);
-        Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("((x = 1) OR (((a = 1) AND (b = 2)) OR ((a = 2) AND (c = 3))))",
-                rewritten.toSql());
-    }
-
-    @Test
-    void test16() {
-        String expr = "a=1 or a=1 or a=1";
-        Expression expression = PARSER.parseExpression(expr);
-        Expression rewritten = OrToIn.INSTANCE.rewriteTree(expression, context);
-        Assertions.assertEquals("(a = 1)",
-                rewritten.toSql());
-    }
 }
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query13.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query13.out
index ef354dbaff4eeb..bcf93db6b5ab66 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query13.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query13.out
@@ -7,9 +7,9 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=() build RFs:RF4 s_store_sk->[ss_store_sk]
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN shuffle] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('D', 'W')) AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((cd_marital_status IN ('D', 'W') AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
+--------------hashJoin[INNER_JOIN shuffle] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
 ----------------PhysicalProject
-------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'M', 'W'))
+------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 --------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=() build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query15.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query15.out
index 212fd68ca76555..ab16eb79d728bb 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query15.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query15.out
@@ -8,7 +8,7 @@ PhysicalResultSink
 ----------PhysicalDistribute[DistributionSpecHash]
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
+----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
 ------------------PhysicalProject
 --------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[cs_sold_date_sk]
 ----------------------PhysicalProject
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query41.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query41.out
index c870e728a39819..c27e19cc9f2387 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query41.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('forest', 'lime', 'maroon', 'navy', 'powder', 'sky', 'slate', 'smoke') AND i_units IN ('Bunch', 'Case', 'Dozen', 'Gross', 'Lb', 'Ounce', 'Pallet', 'Pound')) AND ((((((item.i_category = 'Women') AND i_color IN ('forest', 'lime')) AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('navy', 'slate')) AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('powder', 'sky')) AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) AND i_size IN ('economy', 'small'))))) OR ((i_color IN ('aquamarine', 'dark', 'firebrick', 'frosted', 'papaya', 'peach', 'plum', 'sienna') AND i_units IN ('Box', 'Bundle', 'Carton', 'Cup', 'Dram', 'Each', 'Tbl', 'Ton')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'dark')) AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('frosted', 'plum')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('papaya', 'peach')) AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each')) AND i_size IN ('economy', 'small')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'petite', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'small') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) OR ((i_size IN ('economy', 'small') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each'))) OR ((i_color IN ('powder', 'sky') AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('papaya', 'peach') AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('forest', 'lime') AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((i_color IN ('navy', 'slate') AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR ((i_color IN ('aquamarine', 'dark') AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small'))) OR ((i_color IN ('frosted', 'plum') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query47.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query47.out
index 2bc34ca1076a83..d2fce02a945701 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query47.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query47.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))) and d_year IN (1999, 2000, 2001) and d_year IN (1999, 2000, 2001))
+--------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[store]
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query48.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query48.out
index 06ecefed7e0624..6007be89b374d0 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query48.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query48.out
@@ -16,7 +16,7 @@ PhysicalResultSink
 --------------------------filter((store_sales.ss_net_profit <= 25000.00) and (store_sales.ss_net_profit >= 0.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
 ----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF3
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'Secondary')) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '2 yr Degree'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('2 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('D', 'M', 'S'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'Secondary')) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '2 yr Degree'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('CO', 'GA', 'KS', 'MD', 'MN', 'NC', 'ND', 'NY', 'SD'))
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query53.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query53.out
index 5e987921a5d3f7..8fd5e4b89e46ea 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query53.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197))
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query57.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query57.out
index 91234f18164852..da06fcebfa0dfe 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query57.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query57.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[catalog_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+--------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[call_center]
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query63.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query63.out
index 89a666497689a1..993a0211331f8d 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query63.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233))
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query85.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query85.out
index aca2a36b6a8e3a..0293af606cb791 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query85.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query85.out
@@ -17,8 +17,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF5 wr_returning_cdemo_sk->[cd_demo_sk];RF6 cd_marital_status->[cd_marital_status];RF7 cd_education_status->[cd_education_status]
 ----------------------------PhysicalProject
-------------------------------filter(cd_education_status IN ('Advanced Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'S', 'U'))
---------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6 RF7
+------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6 RF7
 ----------------------------PhysicalProject
 ------------------------------hashJoin[INNER_JOIN bucketShuffle] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('IA', 'NC', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('GA', 'WI', 'WV') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('KY', 'OK', 'VA') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF4 wr_refunded_addr_sk->[ca_address_sk]
 --------------------------------PhysicalProject
@@ -39,7 +38,7 @@ PhysicalResultSink
 ----------------------------------------------filter((date_dim.d_year = 1998))
 ------------------------------------------------PhysicalOlapScan[date_dim]
 ------------------------------------PhysicalProject
---------------------------------------filter(((((cd1.cd_marital_status = 'D') AND (cd1.cd_education_status = 'Primary')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'College'))) OR ((cd1.cd_marital_status = 'U') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'S', 'U'))
+--------------------------------------filter(((((cd1.cd_marital_status = 'D') AND (cd1.cd_education_status = 'Primary')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'College'))) OR ((cd1.cd_marital_status = 'U') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ----------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[reason]
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query88.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query88.out
index 01644900894142..d763e0cebdf7d7 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query88.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query88.out
@@ -24,7 +24,7 @@ PhysicalResultSink
 --------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
 ----------------------------------------PhysicalOlapScan[time_dim]
 --------------------------------PhysicalProject
-----------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+----------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------------PhysicalOlapScan[household_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((store.s_store_name = 'ese'))
@@ -45,7 +45,7 @@ PhysicalResultSink
 --------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
 ----------------------------------------PhysicalOlapScan[time_dim]
 --------------------------------PhysicalProject
-----------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+----------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------------PhysicalOlapScan[household_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((store.s_store_name = 'ese'))
@@ -66,7 +66,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -87,7 +87,7 @@ PhysicalResultSink
 ----------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
 ------------------------------------PhysicalOlapScan[time_dim]
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((store.s_store_name = 'ese'))
@@ -108,7 +108,7 @@ PhysicalResultSink
 --------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
 ----------------------------------PhysicalOlapScan[time_dim]
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+----------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((store.s_store_name = 'ese'))
@@ -129,7 +129,7 @@ PhysicalResultSink
 ------------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
 --------------------------------PhysicalOlapScan[time_dim]
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((store.s_store_name = 'ese'))
@@ -150,7 +150,7 @@ PhysicalResultSink
 ----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
 ------------------------------PhysicalOlapScan[time_dim]
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((store.s_store_name = 'ese'))
@@ -171,7 +171,7 @@ PhysicalResultSink
 --------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
 ----------------------------PhysicalOlapScan[time_dim]
 --------------------PhysicalProject
-----------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+----------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------PhysicalOlapScan[household_demographics]
 ----------------PhysicalProject
 ------------------filter((store.s_store_name = 'ese'))
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query89.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query89.out
index 91ff8765933815..b6df862c67c3af 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query89.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('audio', 'history', 'school-uniforms')) OR (i_category IN ('Men', 'Shoes', 'Sports') AND i_class IN ('pants', 'tennis', 'womens'))) and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Shoes', 'Sports') and i_class IN ('audio', 'history', 'pants', 'school-uniforms', 'tennis', 'womens'))
+------------------------------------------filter(((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('audio', 'history', 'school-uniforms')) OR (i_category IN ('Men', 'Shoes', 'Sports') AND i_class IN ('pants', 'tennis', 'womens'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 2001))
diff --git a/regression-test/data/nereids_hint_tpcds_p0/shape/query91.out b/regression-test/data/nereids_hint_tpcds_p0/shape/query91.out
index 95b8e947317d70..8f6f16ec2d5405 100644
--- a/regression-test/data/nereids_hint_tpcds_p0/shape/query91.out
+++ b/regression-test/data/nereids_hint_tpcds_p0/shape/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like 'Unknown%'))
diff --git a/regression-test/data/nereids_hint_tpch_p0/shape/q19.out b/regression-test/data/nereids_hint_tpch_p0/shape/q19.out
index 940b16c90e40d5..134bae88f41575 100644
--- a/regression-test/data/nereids_hint_tpch_p0/shape/q19.out
+++ b/regression-test/data/nereids_hint_tpch_p0/shape/q19.out
@@ -10,7 +10,7 @@ PhysicalResultSink
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem]
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
 Hint log:
diff --git a/regression-test/data/nereids_hint_tpch_p0/shape/q4.out b/regression-test/data/nereids_hint_tpch_p0/shape/q4.out
index 52feced2463c86..94b49c830c4b45 100644
--- a/regression-test/data/nereids_hint_tpch_p0/shape/q4.out
+++ b/regression-test/data/nereids_hint_tpch_p0/shape/q4.out
@@ -8,13 +8,13 @@ PhysicalResultSink
 ----------PhysicalDistribute[DistributionSpecHash]
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[LEFT_SEMI_JOIN colocated] hashCondition=((lineitem.l_orderkey = orders.o_orderkey)) otherCondition=()
-------------------PhysicalProject
---------------------filter((orders.o_orderdate < '1993-10-01') and (orders.o_orderdate >= '1993-07-01'))
-----------------------PhysicalOlapScan[orders]
+----------------hashJoin[RIGHT_SEMI_JOIN colocated] hashCondition=((lineitem.l_orderkey = orders.o_orderkey)) otherCondition=()
 ------------------PhysicalProject
 --------------------filter((lineitem.l_commitdate < lineitem.l_receiptdate))
 ----------------------PhysicalOlapScan[lineitem]
+------------------PhysicalProject
+--------------------filter((orders.o_orderdate < '1993-10-01') and (orders.o_orderdate >= '1993-07-01'))
+----------------------PhysicalOlapScan[orders]
 
 Hint log:
 Used: leading(lineitem orders )
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/bs_downgrade_shape/query13.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/bs_downgrade_shape/query13.out
index 30208c887cae7a..c0aecbb0023f41 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/bs_downgrade_shape/query13.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/bs_downgrade_shape/query13.out
@@ -14,14 +14,14 @@ PhysicalResultSink
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('D', 'W')) AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((cd_marital_status IN ('D', 'W') AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF1 hd_demo_sk->[ss_hdemo_sk]
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF1 hd_demo_sk->[ss_hdemo_sk]
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=() build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ----------------------------PhysicalProject
 ------------------------------filter((store_sales.ss_net_profit <= 300.00) and (store_sales.ss_net_profit >= 50.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
 --------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF4
 ----------------------------PhysicalProject
-------------------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'M', 'W'))
+------------------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 --------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------PhysicalProject
 --------------------------filter(hd_dep_count IN (1, 3))
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/bs_downgrade_shape/query91.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/bs_downgrade_shape/query91.out
index 624685e9dab961..69fe2228399236 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/bs_downgrade_shape/query91.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/bs_downgrade_shape/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like 'Unknown%'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query13.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query13.out
index 30208c887cae7a..c0aecbb0023f41 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query13.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query13.out
@@ -14,14 +14,14 @@ PhysicalResultSink
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('D', 'W')) AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((cd_marital_status IN ('D', 'W') AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF1 hd_demo_sk->[ss_hdemo_sk]
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF1 hd_demo_sk->[ss_hdemo_sk]
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=() build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ----------------------------PhysicalProject
 ------------------------------filter((store_sales.ss_net_profit <= 300.00) and (store_sales.ss_net_profit >= 50.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
 --------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF4
 ----------------------------PhysicalProject
-------------------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'M', 'W'))
+------------------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 --------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------PhysicalProject
 --------------------------filter(hd_dep_count IN (1, 3))
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query15.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query15.out
index 2de8417f7ab831..d65941c949e46b 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query15.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query15.out
@@ -8,7 +8,7 @@ PhysicalResultSink
 ----------PhysicalDistribute[DistributionSpecHash]
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
+----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
 ------------------PhysicalProject
 --------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[cs_sold_date_sk]
 ----------------------PhysicalProject
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query41.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query41.out
index c870e728a39819..c27e19cc9f2387 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query41.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('forest', 'lime', 'maroon', 'navy', 'powder', 'sky', 'slate', 'smoke') AND i_units IN ('Bunch', 'Case', 'Dozen', 'Gross', 'Lb', 'Ounce', 'Pallet', 'Pound')) AND ((((((item.i_category = 'Women') AND i_color IN ('forest', 'lime')) AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('navy', 'slate')) AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('powder', 'sky')) AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) AND i_size IN ('economy', 'small'))))) OR ((i_color IN ('aquamarine', 'dark', 'firebrick', 'frosted', 'papaya', 'peach', 'plum', 'sienna') AND i_units IN ('Box', 'Bundle', 'Carton', 'Cup', 'Dram', 'Each', 'Tbl', 'Ton')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'dark')) AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('frosted', 'plum')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('papaya', 'peach')) AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each')) AND i_size IN ('economy', 'small')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'petite', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'small') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) OR ((i_size IN ('economy', 'small') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each'))) OR ((i_color IN ('powder', 'sky') AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('papaya', 'peach') AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('forest', 'lime') AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((i_color IN ('navy', 'slate') AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR ((i_color IN ('aquamarine', 'dark') AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small'))) OR ((i_color IN ('frosted', 'plum') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query47.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query47.out
index caec3b20581ed5..0ea84e3ca2b33d 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query47.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query47.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))) and d_year IN (1999, 2000, 2001) and d_year IN (1999, 2000, 2001))
+--------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[store]
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query48.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query48.out
index 3fcfef0d8f68ba..c20cd07f178f50 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query48.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query48.out
@@ -7,23 +7,23 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=() build RFs:RF3 s_store_sk->[ss_store_sk]
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
+--------------hashJoin[INNER_JOIN bucketShuffle] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('ND', 'NY', 'SD') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('GA', 'KS', 'MD') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('CO', 'MN', 'NC') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF2 ss_addr_sk->[ca_address_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('ND', 'NY', 'SD') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('GA', 'KS', 'MD') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('CO', 'MN', 'NC') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF1 ca_address_sk->[ss_addr_sk]
+------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('CO', 'GA', 'KS', 'MD', 'MN', 'NC', 'ND', 'NY', 'SD'))
+--------------------PhysicalOlapScan[customer_address] apply RFs: RF2
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'Secondary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Advanced Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
 --------------------------filter((store_sales.ss_net_profit <= 25000.00) and (store_sales.ss_net_profit >= 0.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
-----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF3
+----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF3
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'Secondary')) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '2 yr Degree'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('2 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('D', 'M', 'S'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'Secondary')) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '2 yr Degree'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
-----------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('CO', 'GA', 'KS', 'MD', 'MN', 'NC', 'ND', 'NY', 'SD'))
-------------------------PhysicalOlapScan[customer_address]
-----------------PhysicalProject
-------------------filter((date_dim.d_year = 2001))
---------------------PhysicalOlapScan[date_dim]
+----------------------filter((date_dim.d_year = 2001))
+------------------------PhysicalOlapScan[date_dim]
 ------------PhysicalProject
 --------------PhysicalOlapScan[store]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query53.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query53.out
index 07d64a35b071ca..fe473000e5966d 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query53.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197))
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query57.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query57.out
index c1b802ebfc4498..356837343861e9 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query57.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query57.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[catalog_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+--------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[call_center]
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query63.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query63.out
index d1807a29db2f0d..8452d151a7d207 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query63.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233))
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query85.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query85.out
index 1781cd24d5b9f5..1ad51b4c22aa79 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query85.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query85.out
@@ -11,12 +11,13 @@ PhysicalResultSink
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=() build RFs:RF9 r_reason_sk->[wr_reason_sk]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF6 wr_returning_cdemo_sk->[cd_demo_sk];RF7 cd_marital_status->[cd_marital_status];RF8 cd_education_status->[cd_education_status]
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF8 ws_web_page_sk->[wp_web_page_sk]
 ------------------------PhysicalProject
---------------------------filter(cd_education_status IN ('Advanced Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'S', 'U'))
-----------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF6 RF7 RF8
+--------------------------PhysicalOlapScan[web_page] apply RFs: RF8
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF5 wp_web_page_sk->[ws_web_page_sk]
+--------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF5 wr_returning_cdemo_sk->[cd_demo_sk];RF6 cd_marital_status->[cd_marital_status];RF7 cd_education_status->[cd_education_status]
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6 RF7
 ----------------------------PhysicalProject
 ------------------------------hashJoin[INNER_JOIN bucketShuffle] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('IA', 'NC', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('GA', 'WI', 'WV') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('KY', 'OK', 'VA') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF4 wr_refunded_addr_sk->[ca_address_sk]
 --------------------------------PhysicalProject
@@ -32,15 +33,13 @@ PhysicalResultSink
 ------------------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF0 d_date_sk->[ws_sold_date_sk]
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((web_sales.ws_net_profit <= 300.00) and (web_sales.ws_net_profit >= 50.00) and (web_sales.ws_sales_price <= 200.00) and (web_sales.ws_sales_price >= 50.00))
-------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF0 RF5
+------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF0
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((date_dim.d_year = 1998))
 ------------------------------------------------PhysicalOlapScan[date_dim]
 ------------------------------------PhysicalProject
---------------------------------------filter(((((cd1.cd_marital_status = 'D') AND (cd1.cd_education_status = 'Primary')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'College'))) OR ((cd1.cd_marital_status = 'U') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'S', 'U'))
+--------------------------------------filter(((((cd1.cd_marital_status = 'D') AND (cd1.cd_education_status = 'Primary')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'College'))) OR ((cd1.cd_marital_status = 'U') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ----------------------------------------PhysicalOlapScan[customer_demographics]
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[web_page]
 --------------------PhysicalProject
 ----------------------PhysicalOlapScan[reason]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query88.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query88.out
index dc3f1ece14f64d..c1d5cc7801f9ef 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query88.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query88.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -43,7 +43,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -63,7 +63,7 @@ PhysicalResultSink
 ----------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
 ------------------------------------PhysicalOlapScan[time_dim]
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((store.s_store_name = 'ese'))
@@ -83,7 +83,7 @@ PhysicalResultSink
 --------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
 ----------------------------------PhysicalOlapScan[time_dim]
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+----------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((store.s_store_name = 'ese'))
@@ -103,7 +103,7 @@ PhysicalResultSink
 ------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
 --------------------------------PhysicalOlapScan[time_dim]
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((store.s_store_name = 'ese'))
@@ -123,7 +123,7 @@ PhysicalResultSink
 ----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
 ------------------------------PhysicalOlapScan[time_dim]
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((store.s_store_name = 'ese'))
@@ -143,7 +143,7 @@ PhysicalResultSink
 --------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
 ----------------------------PhysicalOlapScan[time_dim]
 --------------------PhysicalProject
-----------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+----------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------PhysicalOlapScan[household_demographics]
 ----------------PhysicalProject
 ------------------filter((store.s_store_name = 'ese'))
@@ -163,7 +163,7 @@ PhysicalResultSink
 ------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
 --------------------------PhysicalOlapScan[time_dim]
 ------------------PhysicalProject
---------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------PhysicalOlapScan[household_demographics]
 --------------PhysicalProject
 ----------------filter((store.s_store_name = 'ese'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query89.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query89.out
index 786de940dad5d8..64708542abb732 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query89.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('audio', 'history', 'school-uniforms')) OR (i_category IN ('Men', 'Shoes', 'Sports') AND i_class IN ('pants', 'tennis', 'womens'))) and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Shoes', 'Sports') and i_class IN ('audio', 'history', 'pants', 'school-uniforms', 'tennis', 'womens'))
+------------------------------------------filter(((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('audio', 'history', 'school-uniforms')) OR (i_category IN ('Men', 'Shoes', 'Sports') AND i_class IN ('pants', 'tennis', 'womens'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 2001))
diff --git a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query91.out b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query91.out
index 624685e9dab961..69fe2228399236 100644
--- a/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query91.out
+++ b/regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like 'Unknown%'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query13.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query13.out
index b62a45f1fe22ea..08f8e5ff97a318 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query13.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query13.out
@@ -9,7 +9,7 @@ PhysicalResultSink
 ------------PhysicalProject
 --------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('KS', 'MI', 'SD') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('CO', 'MO', 'ND') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00)))) OR (ca_state IN ('NH', 'OH', 'TX') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))))) build RFs:RF3 ca_address_sk->[ss_addr_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('M', 'S')) AND cd_education_status IN ('4 yr Degree', 'College')) AND ((cd_marital_status IN ('M', 'S') AND cd_education_status IN ('4 yr Degree', 'College')) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=() build RFs:RF1 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
@@ -20,7 +20,7 @@ PhysicalResultSink
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store]
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))) and cd_education_status IN ('4 yr Degree', 'College', 'Unknown') and cd_marital_status IN ('D', 'M', 'S'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter(hd_dep_count IN (1, 3))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query15.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query15.out
index 7b0fd9b10fd861..3190fe50914cc0 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query15.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query15.out
@@ -10,7 +10,7 @@ PhysicalResultSink
 --------------PhysicalProject
 ----------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[cs_sold_date_sk]
 ------------------PhysicalProject
---------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00)))
+--------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00)))
 ----------------------PhysicalProject
 ------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=()
 --------------------------PhysicalProject
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query41.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query41.out
index ff811ef082cc23..34081b60b900b2 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query41.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('aquamarine', 'blue', 'chartreuse', 'chiffon', 'dodger', 'gainsboro', 'tan', 'violet') AND i_units IN ('Bunch', 'Dozen', 'Each', 'Ounce', 'Oz', 'Pound', 'Ton', 'Tsp')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'gainsboro')) AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('chiffon', 'violet')) AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('blue', 'chartreuse')) AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) AND i_size IN ('economy', 'medium'))))) OR ((i_color IN ('almond', 'blanched', 'indian', 'lime', 'peru', 'saddle', 'spring', 'tomato') AND i_units IN ('Box', 'Carton', 'Case', 'Dram', 'Gram', 'Pallet', 'Tbl', 'Unknown')) AND ((((((item.i_category = 'Women') AND i_color IN ('blanched', 'tomato')) AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('almond', 'lime')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('peru', 'saddle')) AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown')) AND i_size IN ('economy', 'medium')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'medium', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'medium') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) OR ((i_size IN ('economy', 'medium') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown'))) OR ((i_color IN ('blue', 'chartreuse') AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('peru', 'saddle') AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('aquamarine', 'gainsboro') AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((i_color IN ('chiffon', 'violet') AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR ((i_color IN ('blanched', 'tomato') AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium'))) OR ((i_color IN ('almond', 'lime') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query47.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query47.out
index 0182bbf46eb817..e2d0ecdb0ba6ac 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query47.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query47.out
@@ -23,7 +23,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[item]
 --------------------------------PhysicalProject
-----------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+----------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query48.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query48.out
index 338a70100eb21b..255cb1f3b3279e 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query48.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query48.out
@@ -18,7 +18,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[store]
 --------------------PhysicalProject
-----------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'U', 'W'))
+----------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 ------------------------PhysicalOlapScan[customer_demographics]
 ----------------PhysicalProject
 ------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query53.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query53.out
index 93289fca48e4ef..d14fe74213eb0d 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query53.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query57.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query57.out
index a05f8e84e68830..10cbd1fa9a0489 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query57.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query57.out
@@ -23,7 +23,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[item]
 --------------------------------PhysicalProject
-----------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))) and d_year IN (1998, 1999, 2000) and d_year IN (1998, 1999, 2000))
+----------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))))
 ------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[call_center]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query63.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query63.out
index 3bd844ce72c196..b16aa6edd4a56d 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query63.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query85.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query85.out
index 590589c61a42a0..0de3c1e87649c1 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query85.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query85.out
@@ -15,25 +15,24 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF7 ca_address_sk->[wr_refunded_addr_sk]
 ----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF4 cd_demo_sk->[wr_returning_cdemo_sk];RF5 cd_marital_status->[cd_marital_status];RF6 cd_education_status->[cd_education_status]
+------------------------------hashJoin[INNER_JOIN shuffle] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk) and (cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF4 cd_marital_status->[cd_marital_status];RF5 cd_education_status->[cd_education_status];RF6 cd_demo_sk->[wr_refunded_cdemo_sk]
 --------------------------------PhysicalProject
-----------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF3 cd_demo_sk->[wr_refunded_cdemo_sk]
+----------------------------------hashJoin[INNER_JOIN shuffle] hashCondition=((cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF3 cd_demo_sk->[wr_returning_cdemo_sk]
 ------------------------------------PhysicalProject
 --------------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=()
 ----------------------------------------PhysicalProject
 ------------------------------------------hashJoin[INNER_JOIN colocated] hashCondition=((web_sales.ws_item_sk = web_returns.wr_item_sk) and (web_sales.ws_order_number = web_returns.wr_order_number)) otherCondition=() build RFs:RF0 ws_item_sk->[wr_item_sk];RF1 ws_order_number->[wr_order_number]
 --------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF0 RF1 RF3 RF4 RF7
+----------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF0 RF1 RF3 RF6 RF7
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((web_sales.ws_net_profit <= 300.00) and (web_sales.ws_net_profit >= 50.00) and (web_sales.ws_sales_price <= 200.00) and (web_sales.ws_sales_price >= 50.00))
 ------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF8
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[web_page]
 ------------------------------------PhysicalProject
---------------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
-----------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6
+--------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF4 RF5
 --------------------------------PhysicalProject
-----------------------------------filter(cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
+----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ------------------------------------PhysicalOlapScan[customer_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('DE', 'FL', 'ID', 'IL', 'IN', 'MT', 'ND', 'OH', 'TX'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query88.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query88.out
index dc879d6daa5a4b..0bc35393abd55f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query88.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query88.out
@@ -20,7 +20,7 @@ PhysicalResultSink
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF21 RF22 RF23
 ----------------------------------PhysicalProject
-------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalProject
 --------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
@@ -40,7 +40,7 @@ PhysicalResultSink
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF18 RF19 RF20
 ----------------------------------PhysicalProject
-------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalProject
 --------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
@@ -60,7 +60,7 @@ PhysicalResultSink
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[store_sales] apply RFs: RF15 RF16 RF17
 --------------------------------PhysicalProject
-----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------------PhysicalOlapScan[household_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
@@ -80,7 +80,7 @@ PhysicalResultSink
 ------------------------------PhysicalProject
 --------------------------------PhysicalOlapScan[store_sales] apply RFs: RF12 RF13 RF14
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
@@ -100,7 +100,7 @@ PhysicalResultSink
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store_sales] apply RFs: RF9 RF10 RF11
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
@@ -120,7 +120,7 @@ PhysicalResultSink
 --------------------------PhysicalProject
 ----------------------------PhysicalOlapScan[store_sales] apply RFs: RF6 RF7 RF8
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
@@ -140,7 +140,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[store_sales] apply RFs: RF3 RF4 RF5
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
@@ -160,7 +160,7 @@ PhysicalResultSink
 ----------------------PhysicalProject
 ------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query89.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query89.out
index c709c4df5fe097..e1c1fd9222d84f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query89.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))) and i_category IN ('Electronics', 'Jewelry', 'Men', 'Music', 'Shoes', 'Women') and i_class IN ('accessories', 'athletic', 'maternity', 'portable', 'rock', 'semi-precious'))
+------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query91.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query91.out
index aa211a9f494891..6e532bb76fc3d7 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query91.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/noStatsRfPrune/query91.out
@@ -33,7 +33,7 @@ PhysicalResultSink
 ------------------------------filter((customer_address.ca_gmt_offset = -6.00))
 --------------------------------PhysicalOlapScan[customer_address]
 ------------------------PhysicalProject
---------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+--------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter((hd_buy_potential like '1001-5000%'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query13.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query13.out
index 61f8590deca15c..f6ffa6432e6645 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query13.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query13.out
@@ -9,7 +9,7 @@ PhysicalResultSink
 ------------PhysicalProject
 --------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('KS', 'MI', 'SD') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('CO', 'MO', 'ND') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00)))) OR (ca_state IN ('NH', 'OH', 'TX') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))))) build RFs:RF3 ca_address_sk->[ss_addr_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('M', 'S')) AND cd_education_status IN ('4 yr Degree', 'College')) AND ((cd_marital_status IN ('M', 'S') AND cd_education_status IN ('4 yr Degree', 'College')) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=() build RFs:RF1 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
@@ -20,7 +20,7 @@ PhysicalResultSink
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store]
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))) and cd_education_status IN ('4 yr Degree', 'College', 'Unknown') and cd_marital_status IN ('D', 'M', 'S'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter(hd_dep_count IN (1, 3))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query15.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query15.out
index 1fba646d62b40a..cbfedc9459a274 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query15.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query15.out
@@ -10,7 +10,7 @@ PhysicalResultSink
 --------------PhysicalProject
 ----------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[cs_sold_date_sk]
 ------------------PhysicalProject
---------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF1 ca_address_sk->[c_current_addr_sk]
+--------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF1 ca_address_sk->[c_current_addr_sk]
 ----------------------PhysicalProject
 ------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=() build RFs:RF0 c_customer_sk->[cs_bill_customer_sk]
 --------------------------PhysicalProject
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query41.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query41.out
index ff811ef082cc23..34081b60b900b2 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query41.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('aquamarine', 'blue', 'chartreuse', 'chiffon', 'dodger', 'gainsboro', 'tan', 'violet') AND i_units IN ('Bunch', 'Dozen', 'Each', 'Ounce', 'Oz', 'Pound', 'Ton', 'Tsp')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'gainsboro')) AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('chiffon', 'violet')) AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('blue', 'chartreuse')) AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) AND i_size IN ('economy', 'medium'))))) OR ((i_color IN ('almond', 'blanched', 'indian', 'lime', 'peru', 'saddle', 'spring', 'tomato') AND i_units IN ('Box', 'Carton', 'Case', 'Dram', 'Gram', 'Pallet', 'Tbl', 'Unknown')) AND ((((((item.i_category = 'Women') AND i_color IN ('blanched', 'tomato')) AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('almond', 'lime')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('peru', 'saddle')) AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown')) AND i_size IN ('economy', 'medium')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'medium', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'medium') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) OR ((i_size IN ('economy', 'medium') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown'))) OR ((i_color IN ('blue', 'chartreuse') AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('peru', 'saddle') AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('aquamarine', 'gainsboro') AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((i_color IN ('chiffon', 'violet') AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR ((i_color IN ('blanched', 'tomato') AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium'))) OR ((i_color IN ('almond', 'lime') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query47.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query47.out
index b6f046eb01fe81..b27001e19a607d 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query47.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query47.out
@@ -23,7 +23,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[item]
 --------------------------------PhysicalProject
-----------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+----------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query48.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query48.out
index ed7ed3b4bdf669..283f05fff6d32c 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query48.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query48.out
@@ -18,7 +18,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[store]
 --------------------PhysicalProject
-----------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'U', 'W'))
+----------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 ------------------------PhysicalOlapScan[customer_demographics]
 ----------------PhysicalProject
 ------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query53.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query53.out
index 81e6091b663bf7..7dbd34d228fe3f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query53.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query57.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query57.out
index 9b61dc54e2a91e..018e37ee77fbfa 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query57.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query57.out
@@ -23,7 +23,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[item]
 --------------------------------PhysicalProject
-----------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))) and d_year IN (1998, 1999, 2000) and d_year IN (1998, 1999, 2000))
+----------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))))
 ------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[call_center]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query63.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query63.out
index 2cd49bd8c40786..c5cea55eb7b009 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query63.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query85.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query85.out
index 08e59c1e36507e..54835db0dc8817 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query85.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query85.out
@@ -15,25 +15,24 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF7 ca_address_sk->[wr_refunded_addr_sk]
 ----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF4 cd_demo_sk->[wr_returning_cdemo_sk];RF5 cd_marital_status->[cd_marital_status];RF6 cd_education_status->[cd_education_status]
+------------------------------hashJoin[INNER_JOIN shuffle] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk) and (cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF4 cd_marital_status->[cd_marital_status];RF5 cd_education_status->[cd_education_status];RF6 cd_demo_sk->[wr_refunded_cdemo_sk]
 --------------------------------PhysicalProject
-----------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF3 cd_demo_sk->[wr_refunded_cdemo_sk]
+----------------------------------hashJoin[INNER_JOIN shuffle] hashCondition=((cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF3 cd_demo_sk->[wr_returning_cdemo_sk]
 ------------------------------------PhysicalProject
 --------------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF2 wp_web_page_sk->[ws_web_page_sk]
 ----------------------------------------PhysicalProject
 ------------------------------------------hashJoin[INNER_JOIN colocated] hashCondition=((web_sales.ws_item_sk = web_returns.wr_item_sk) and (web_sales.ws_order_number = web_returns.wr_order_number)) otherCondition=() build RFs:RF0 ws_item_sk->[wr_item_sk];RF1 ws_order_number->[wr_order_number]
 --------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF0 RF1 RF3 RF4 RF7 RF9
+----------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF0 RF1 RF3 RF6 RF7 RF9
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((web_sales.ws_net_profit <= 300.00) and (web_sales.ws_net_profit >= 50.00) and (web_sales.ws_sales_price <= 200.00) and (web_sales.ws_sales_price >= 50.00))
 ------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF2 RF8
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[web_page]
 ------------------------------------PhysicalProject
---------------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
-----------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6
+--------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF4 RF5
 --------------------------------PhysicalProject
-----------------------------------filter(cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
+----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ------------------------------------PhysicalOlapScan[customer_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('DE', 'FL', 'ID', 'IL', 'IN', 'MT', 'ND', 'OH', 'TX'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query88.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query88.out
index dc879d6daa5a4b..0bc35393abd55f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query88.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query88.out
@@ -20,7 +20,7 @@ PhysicalResultSink
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF21 RF22 RF23
 ----------------------------------PhysicalProject
-------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalProject
 --------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
@@ -40,7 +40,7 @@ PhysicalResultSink
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF18 RF19 RF20
 ----------------------------------PhysicalProject
-------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalProject
 --------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
@@ -60,7 +60,7 @@ PhysicalResultSink
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[store_sales] apply RFs: RF15 RF16 RF17
 --------------------------------PhysicalProject
-----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------------PhysicalOlapScan[household_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
@@ -80,7 +80,7 @@ PhysicalResultSink
 ------------------------------PhysicalProject
 --------------------------------PhysicalOlapScan[store_sales] apply RFs: RF12 RF13 RF14
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
@@ -100,7 +100,7 @@ PhysicalResultSink
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store_sales] apply RFs: RF9 RF10 RF11
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
@@ -120,7 +120,7 @@ PhysicalResultSink
 --------------------------PhysicalProject
 ----------------------------PhysicalOlapScan[store_sales] apply RFs: RF6 RF7 RF8
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
@@ -140,7 +140,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[store_sales] apply RFs: RF3 RF4 RF5
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
@@ -160,7 +160,7 @@ PhysicalResultSink
 ----------------------PhysicalProject
 ------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query89.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query89.out
index 661b47d0ea980a..35a90cb94290b7 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query89.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))) and i_category IN ('Electronics', 'Jewelry', 'Men', 'Music', 'Shoes', 'Women') and i_class IN ('accessories', 'athletic', 'maternity', 'portable', 'rock', 'semi-precious'))
+------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query91.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query91.out
index c19b43be01a9df..d165c286c01e50 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query91.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/no_stats_shape/query91.out
@@ -33,7 +33,7 @@ PhysicalResultSink
 ------------------------------filter((customer_address.ca_gmt_offset = -6.00))
 --------------------------------PhysicalOlapScan[customer_address]
 ------------------------PhysicalProject
---------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+--------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter((hd_buy_potential like '1001-5000%'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query13.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query13.out
index f3c8db3bfc436d..1210eca43f9d3f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query13.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query13.out
@@ -7,9 +7,9 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=()
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('M', 'S')) AND cd_education_status IN ('4 yr Degree', 'College')) AND ((cd_marital_status IN ('M', 'S') AND cd_education_status IN ('4 yr Degree', 'College')) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
+--------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
 ----------------PhysicalProject
-------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))) and cd_education_status IN ('4 yr Degree', 'College', 'Unknown') and cd_marital_status IN ('D', 'M', 'S'))
+------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
 --------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=() build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query15.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query15.out
index 685f61ffed3387..ed2ea026a241c9 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query15.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query15.out
@@ -8,7 +8,7 @@ PhysicalResultSink
 ----------PhysicalDistribute[DistributionSpecHash]
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
+----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
 ------------------PhysicalProject
 --------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[cs_sold_date_sk]
 ----------------------PhysicalProject
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query41.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query41.out
index ff811ef082cc23..34081b60b900b2 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query41.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('aquamarine', 'blue', 'chartreuse', 'chiffon', 'dodger', 'gainsboro', 'tan', 'violet') AND i_units IN ('Bunch', 'Dozen', 'Each', 'Ounce', 'Oz', 'Pound', 'Ton', 'Tsp')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'gainsboro')) AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('chiffon', 'violet')) AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('blue', 'chartreuse')) AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) AND i_size IN ('economy', 'medium'))))) OR ((i_color IN ('almond', 'blanched', 'indian', 'lime', 'peru', 'saddle', 'spring', 'tomato') AND i_units IN ('Box', 'Carton', 'Case', 'Dram', 'Gram', 'Pallet', 'Tbl', 'Unknown')) AND ((((((item.i_category = 'Women') AND i_color IN ('blanched', 'tomato')) AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('almond', 'lime')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('peru', 'saddle')) AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown')) AND i_size IN ('economy', 'medium')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'medium', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'medium') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) OR ((i_size IN ('economy', 'medium') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown'))) OR ((i_color IN ('blue', 'chartreuse') AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('peru', 'saddle') AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('aquamarine', 'gainsboro') AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((i_color IN ('chiffon', 'violet') AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR ((i_color IN ('blanched', 'tomato') AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium'))) OR ((i_color IN ('almond', 'lime') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query47.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query47.out
index e115c8751281e0..52bd4fa6fbf623 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query47.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query47.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+--------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[item]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query48.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query48.out
index 476aa9dd8793af..b25d7ab6b754a2 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query48.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query48.out
@@ -7,23 +7,23 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=()
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
+--------------hashJoin[INNER_JOIN bucketShuffle] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF2 ss_addr_sk->[ca_address_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF1 ca_address_sk->[ss_addr_sk]
+------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
+--------------------PhysicalOlapScan[customer_address] apply RFs: RF2
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
 --------------------------filter((store_sales.ss_net_profit <= 25000.00) and (store_sales.ss_net_profit >= 0.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
-----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
+----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'U', 'W'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
-----------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
-------------------------PhysicalOlapScan[customer_address]
-----------------PhysicalProject
-------------------filter((date_dim.d_year = 1999))
---------------------PhysicalOlapScan[date_dim]
+----------------------filter((date_dim.d_year = 1999))
+------------------------PhysicalOlapScan[date_dim]
 ------------PhysicalProject
 --------------PhysicalOlapScan[store]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query53.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query53.out
index 93289fca48e4ef..d14fe74213eb0d 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query53.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query57.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query57.out
index 053e8bfc4c7f54..60276268fc3224 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query57.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query57.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[catalog_sales] apply RFs: RF0
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))) and d_year IN (1998, 1999, 2000) and d_year IN (1998, 1999, 2000))
+--------------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[item]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query63.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query63.out
index 3bd844ce72c196..b16aa6edd4a56d 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query63.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query85.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query85.out
index d08017427d5c94..74ace999b87a48 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query85.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query85.out
@@ -9,18 +9,17 @@ PhysicalResultSink
 ------------PhysicalDistribute[DistributionSpecHash]
 --------------hashAgg[LOCAL]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=()
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=()
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=()
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF6 wr_returning_cdemo_sk->[cd_demo_sk];RF7 cd_marital_status->[cd_marital_status];RF8 cd_education_status->[cd_education_status]
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF5 wr_returning_cdemo_sk->[cd_demo_sk];RF6 cd_marital_status->[cd_marital_status];RF7 cd_education_status->[cd_education_status]
-----------------------------PhysicalProject
-------------------------------filter(cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
---------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6 RF7
+--------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF6 RF7 RF8
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=()
 ----------------------------PhysicalProject
 ------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF4 wr_refunded_cdemo_sk->[cd_demo_sk]
 --------------------------------PhysicalProject
-----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
+----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF4
 --------------------------------PhysicalProject
 ----------------------------------hashJoin[INNER_JOIN bucketShuffle] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF3 wr_refunded_addr_sk->[ca_address_sk]
@@ -39,8 +38,8 @@ PhysicalResultSink
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((date_dim.d_year = 2000))
 ------------------------------------------------PhysicalOlapScan[date_dim]
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[reason]
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[web_page]
 --------------------PhysicalProject
-----------------------PhysicalOlapScan[web_page]
+----------------------PhysicalOlapScan[reason]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query88.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query88.out
index bca8b0d069014b..af35685d6e46ac 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query88.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query88.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -43,7 +43,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -63,7 +63,7 @@ PhysicalResultSink
 ----------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
 ------------------------------------PhysicalOlapScan[time_dim]
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((store.s_store_name = 'ese'))
@@ -83,7 +83,7 @@ PhysicalResultSink
 --------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
 ----------------------------------PhysicalOlapScan[time_dim]
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((store.s_store_name = 'ese'))
@@ -103,7 +103,7 @@ PhysicalResultSink
 ------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
 --------------------------------PhysicalOlapScan[time_dim]
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((store.s_store_name = 'ese'))
@@ -123,7 +123,7 @@ PhysicalResultSink
 ----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
 ------------------------------PhysicalOlapScan[time_dim]
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((store.s_store_name = 'ese'))
@@ -143,7 +143,7 @@ PhysicalResultSink
 --------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
 ----------------------------PhysicalOlapScan[time_dim]
 --------------------PhysicalProject
-----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------PhysicalOlapScan[household_demographics]
 ----------------PhysicalProject
 ------------------filter((store.s_store_name = 'ese'))
@@ -163,7 +163,7 @@ PhysicalResultSink
 ------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
 --------------------------PhysicalOlapScan[time_dim]
 ------------------PhysicalProject
---------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------PhysicalOlapScan[household_demographics]
 --------------PhysicalProject
 ----------------filter((store.s_store_name = 'ese'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query89.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query89.out
index c709c4df5fe097..e1c1fd9222d84f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query89.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))) and i_category IN ('Electronics', 'Jewelry', 'Men', 'Music', 'Shoes', 'Women') and i_class IN ('accessories', 'athletic', 'maternity', 'portable', 'rock', 'semi-precious'))
+------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query91.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query91.out
index e2a4ed89af442d..2788bd2d8cff0c 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query91.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/rf_prune/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like '1001-5000%'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out
index 17cd82b3e1cf75..357029ffd2214f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query13.out
@@ -7,9 +7,9 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=() build RFs:RF4 s_store_sk->[ss_store_sk]
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('M', 'S')) AND cd_education_status IN ('4 yr Degree', 'College')) AND ((cd_marital_status IN ('M', 'S') AND cd_education_status IN ('4 yr Degree', 'College')) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
+--------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
 ----------------PhysicalProject
-------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))) and cd_education_status IN ('4 yr Degree', 'College', 'Unknown') and cd_marital_status IN ('D', 'M', 'S'))
+------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
 --------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=() build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query15.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query15.out
index 685f61ffed3387..ed2ea026a241c9 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query15.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query15.out
@@ -8,7 +8,7 @@ PhysicalResultSink
 ----------PhysicalDistribute[DistributionSpecHash]
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
+----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
 ------------------PhysicalProject
 --------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[cs_sold_date_sk]
 ----------------------PhysicalProject
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query41.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query41.out
index ff811ef082cc23..34081b60b900b2 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query41.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('aquamarine', 'blue', 'chartreuse', 'chiffon', 'dodger', 'gainsboro', 'tan', 'violet') AND i_units IN ('Bunch', 'Dozen', 'Each', 'Ounce', 'Oz', 'Pound', 'Ton', 'Tsp')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'gainsboro')) AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('chiffon', 'violet')) AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('blue', 'chartreuse')) AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) AND i_size IN ('economy', 'medium'))))) OR ((i_color IN ('almond', 'blanched', 'indian', 'lime', 'peru', 'saddle', 'spring', 'tomato') AND i_units IN ('Box', 'Carton', 'Case', 'Dram', 'Gram', 'Pallet', 'Tbl', 'Unknown')) AND ((((((item.i_category = 'Women') AND i_color IN ('blanched', 'tomato')) AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('almond', 'lime')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('peru', 'saddle')) AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown')) AND i_size IN ('economy', 'medium')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'medium', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'medium') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) OR ((i_size IN ('economy', 'medium') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown'))) OR ((i_color IN ('blue', 'chartreuse') AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('peru', 'saddle') AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('aquamarine', 'gainsboro') AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((i_color IN ('chiffon', 'violet') AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR ((i_color IN ('blanched', 'tomato') AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium'))) OR ((i_color IN ('almond', 'lime') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query47.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query47.out
index 7a668b06c433e5..f33181c085733c 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query47.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query47.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+--------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[item]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out
index c81868cacca7a6..0bb694c50c5abe 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query48.out
@@ -7,23 +7,23 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=() build RFs:RF3 s_store_sk->[ss_store_sk]
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
+--------------hashJoin[INNER_JOIN bucketShuffle] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF2 ss_addr_sk->[ca_address_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF1 ca_address_sk->[ss_addr_sk]
+------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
+--------------------PhysicalOlapScan[customer_address] apply RFs: RF2
+----------------PhysicalProject
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
 --------------------------filter((store_sales.ss_net_profit <= 25000.00) and (store_sales.ss_net_profit >= 0.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
-----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF3
+----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF3
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'U', 'W'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
-----------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
-------------------------PhysicalOlapScan[customer_address]
-----------------PhysicalProject
-------------------filter((date_dim.d_year = 1999))
---------------------PhysicalOlapScan[date_dim]
+----------------------filter((date_dim.d_year = 1999))
+------------------------PhysicalOlapScan[date_dim]
 ------------PhysicalProject
 --------------PhysicalOlapScan[store]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query53.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query53.out
index 81e6091b663bf7..7dbd34d228fe3f 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query53.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query57.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query57.out
index 7bbcf019701d4d..15dda452ebc984 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query57.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query57.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[catalog_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))) and d_year IN (1998, 1999, 2000) and d_year IN (1998, 1999, 2000))
+--------------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[item]
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query63.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query63.out
index 2cd49bd8c40786..c5cea55eb7b009 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query63.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query85.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query85.out
index 8e543215ca9ce5..da46d54e2f8be5 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query85.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query85.out
@@ -9,18 +9,17 @@ PhysicalResultSink
 ------------PhysicalDistribute[DistributionSpecHash]
 --------------hashAgg[LOCAL]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF9 wp_web_page_sk->[ws_web_page_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=() build RFs:RF9 r_reason_sk->[wr_reason_sk]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=() build RFs:RF8 r_reason_sk->[wr_reason_sk]
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF6 wr_returning_cdemo_sk->[cd_demo_sk];RF7 cd_marital_status->[cd_marital_status];RF8 cd_education_status->[cd_education_status]
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF5 wr_returning_cdemo_sk->[cd_demo_sk];RF6 cd_marital_status->[cd_marital_status];RF7 cd_education_status->[cd_education_status]
-----------------------------PhysicalProject
-------------------------------filter(cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
---------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6 RF7
+--------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF6 RF7 RF8
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF5 wp_web_page_sk->[ws_web_page_sk]
 ----------------------------PhysicalProject
 ------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF4 wr_refunded_cdemo_sk->[cd_demo_sk]
 --------------------------------PhysicalProject
-----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
+----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF4
 --------------------------------PhysicalProject
 ----------------------------------hashJoin[INNER_JOIN bucketShuffle] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF3 wr_refunded_addr_sk->[ca_address_sk]
@@ -30,17 +29,17 @@ PhysicalResultSink
 ------------------------------------PhysicalProject
 --------------------------------------hashJoin[INNER_JOIN colocated] hashCondition=((web_sales.ws_item_sk = web_returns.wr_item_sk) and (web_sales.ws_order_number = web_returns.wr_order_number)) otherCondition=() build RFs:RF1 ws_item_sk->[wr_item_sk];RF2 ws_order_number->[wr_order_number]
 ----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF1 RF2 RF8
+------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF1 RF2 RF9
 ----------------------------------------PhysicalProject
 ------------------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF0 d_date_sk->[ws_sold_date_sk]
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((web_sales.ws_net_profit <= 300.00) and (web_sales.ws_net_profit >= 50.00) and (web_sales.ws_sales_price <= 200.00) and (web_sales.ws_sales_price >= 50.00))
-------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF0 RF9
+------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF0 RF5
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((date_dim.d_year = 2000))
 ------------------------------------------------PhysicalOlapScan[date_dim]
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[reason]
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[web_page]
 --------------------PhysicalProject
-----------------------PhysicalOlapScan[web_page]
+----------------------PhysicalOlapScan[reason]
 
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query88.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query88.out
index bca8b0d069014b..af35685d6e46ac 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query88.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query88.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -43,7 +43,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -63,7 +63,7 @@ PhysicalResultSink
 ----------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
 ------------------------------------PhysicalOlapScan[time_dim]
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((store.s_store_name = 'ese'))
@@ -83,7 +83,7 @@ PhysicalResultSink
 --------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
 ----------------------------------PhysicalOlapScan[time_dim]
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((store.s_store_name = 'ese'))
@@ -103,7 +103,7 @@ PhysicalResultSink
 ------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
 --------------------------------PhysicalOlapScan[time_dim]
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((store.s_store_name = 'ese'))
@@ -123,7 +123,7 @@ PhysicalResultSink
 ----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
 ------------------------------PhysicalOlapScan[time_dim]
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((store.s_store_name = 'ese'))
@@ -143,7 +143,7 @@ PhysicalResultSink
 --------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
 ----------------------------PhysicalOlapScan[time_dim]
 --------------------PhysicalProject
-----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------PhysicalOlapScan[household_demographics]
 ----------------PhysicalProject
 ------------------filter((store.s_store_name = 'ese'))
@@ -163,7 +163,7 @@ PhysicalResultSink
 ------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
 --------------------------PhysicalOlapScan[time_dim]
 ------------------PhysicalProject
---------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------PhysicalOlapScan[household_demographics]
 --------------PhysicalProject
 ----------------filter((store.s_store_name = 'ese'))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query89.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query89.out
index 661b47d0ea980a..35a90cb94290b7 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query89.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))) and i_category IN ('Electronics', 'Jewelry', 'Men', 'Music', 'Shoes', 'Women') and i_class IN ('accessories', 'athletic', 'maternity', 'portable', 'rock', 'semi-precious'))
+------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query91.out b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query91.out
index 6f3970cbb29d50..ca8fac70d693aa 100644
--- a/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query91.out
+++ b/regression-test/data/nereids_tpcds_shape_sf100_p0/shape/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like '1001-5000%'))
diff --git a/regression-test/data/nereids_tpch_shape_sf1000_p0/nostats_rf_prune/q19.out b/regression-test/data/nereids_tpch_shape_sf1000_p0/nostats_rf_prune/q19.out
index bf86e68a7f9837..60e7b8446bd1a0 100644
--- a/regression-test/data/nereids_tpch_shape_sf1000_p0/nostats_rf_prune/q19.out
+++ b/regression-test/data/nereids_tpch_shape_sf1000_p0/nostats_rf_prune/q19.out
@@ -10,6 +10,6 @@ PhysicalResultSink
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem] apply RFs: RF0
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
diff --git a/regression-test/data/nereids_tpch_shape_sf1000_p0/rf_prune/q19.out b/regression-test/data/nereids_tpch_shape_sf1000_p0/rf_prune/q19.out
index bf86e68a7f9837..60e7b8446bd1a0 100644
--- a/regression-test/data/nereids_tpch_shape_sf1000_p0/rf_prune/q19.out
+++ b/regression-test/data/nereids_tpch_shape_sf1000_p0/rf_prune/q19.out
@@ -10,6 +10,6 @@ PhysicalResultSink
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem] apply RFs: RF0
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
diff --git a/regression-test/data/nereids_tpch_shape_sf1000_p0/shape/q19.out b/regression-test/data/nereids_tpch_shape_sf1000_p0/shape/q19.out
index bf86e68a7f9837..60e7b8446bd1a0 100644
--- a/regression-test/data/nereids_tpch_shape_sf1000_p0/shape/q19.out
+++ b/regression-test/data/nereids_tpch_shape_sf1000_p0/shape/q19.out
@@ -10,6 +10,6 @@ PhysicalResultSink
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem] apply RFs: RF0
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
diff --git a/regression-test/data/nereids_tpch_shape_sf1000_p0/shape_no_stats/q19.out b/regression-test/data/nereids_tpch_shape_sf1000_p0/shape_no_stats/q19.out
index bf86e68a7f9837..60e7b8446bd1a0 100644
--- a/regression-test/data/nereids_tpch_shape_sf1000_p0/shape_no_stats/q19.out
+++ b/regression-test/data/nereids_tpch_shape_sf1000_p0/shape_no_stats/q19.out
@@ -10,6 +10,6 @@ PhysicalResultSink
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem] apply RFs: RF0
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
diff --git a/regression-test/data/new_shapes_p0/hint_tpch/shape/q19.out b/regression-test/data/new_shapes_p0/hint_tpch/shape/q19.out
index 940b16c90e40d5..134bae88f41575 100644
--- a/regression-test/data/new_shapes_p0/hint_tpch/shape/q19.out
+++ b/regression-test/data/new_shapes_p0/hint_tpch/shape/q19.out
@@ -10,7 +10,7 @@ PhysicalResultSink
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem]
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
 Hint log:
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query13.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query13.out
index b62a45f1fe22ea..08f8e5ff97a318 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query13.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query13.out
@@ -9,7 +9,7 @@ PhysicalResultSink
 ------------PhysicalProject
 --------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('KS', 'MI', 'SD') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('CO', 'MO', 'ND') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00)))) OR (ca_state IN ('NH', 'OH', 'TX') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))))) build RFs:RF3 ca_address_sk->[ss_addr_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('M', 'S')) AND cd_education_status IN ('4 yr Degree', 'College')) AND ((cd_marital_status IN ('M', 'S') AND cd_education_status IN ('4 yr Degree', 'College')) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=() build RFs:RF1 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
@@ -20,7 +20,7 @@ PhysicalResultSink
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store]
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))) and cd_education_status IN ('4 yr Degree', 'College', 'Unknown') and cd_marital_status IN ('D', 'M', 'S'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter(hd_dep_count IN (1, 3))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query15.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query15.out
index 7b0fd9b10fd861..3190fe50914cc0 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query15.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query15.out
@@ -10,7 +10,7 @@ PhysicalResultSink
 --------------PhysicalProject
 ----------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[cs_sold_date_sk]
 ------------------PhysicalProject
---------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00)))
+--------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00)))
 ----------------------PhysicalProject
 ------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=()
 --------------------------PhysicalProject
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query41.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query41.out
index ff811ef082cc23..34081b60b900b2 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query41.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('aquamarine', 'blue', 'chartreuse', 'chiffon', 'dodger', 'gainsboro', 'tan', 'violet') AND i_units IN ('Bunch', 'Dozen', 'Each', 'Ounce', 'Oz', 'Pound', 'Ton', 'Tsp')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'gainsboro')) AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('chiffon', 'violet')) AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('blue', 'chartreuse')) AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) AND i_size IN ('economy', 'medium'))))) OR ((i_color IN ('almond', 'blanched', 'indian', 'lime', 'peru', 'saddle', 'spring', 'tomato') AND i_units IN ('Box', 'Carton', 'Case', 'Dram', 'Gram', 'Pallet', 'Tbl', 'Unknown')) AND ((((((item.i_category = 'Women') AND i_color IN ('blanched', 'tomato')) AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('almond', 'lime')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('peru', 'saddle')) AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown')) AND i_size IN ('economy', 'medium')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'medium', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'medium') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) OR ((i_size IN ('economy', 'medium') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown'))) OR ((i_color IN ('blue', 'chartreuse') AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('peru', 'saddle') AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('aquamarine', 'gainsboro') AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((i_color IN ('chiffon', 'violet') AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR ((i_color IN ('blanched', 'tomato') AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium'))) OR ((i_color IN ('almond', 'lime') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query47.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query47.out
index 0182bbf46eb817..e2d0ecdb0ba6ac 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query47.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query47.out
@@ -23,7 +23,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[item]
 --------------------------------PhysicalProject
-----------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+----------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query48.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query48.out
index 338a70100eb21b..255cb1f3b3279e 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query48.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query48.out
@@ -18,7 +18,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[store]
 --------------------PhysicalProject
-----------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'U', 'W'))
+----------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 ------------------------PhysicalOlapScan[customer_demographics]
 ----------------PhysicalProject
 ------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query53.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query53.out
index 93289fca48e4ef..d14fe74213eb0d 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query53.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query57.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query57.out
index a05f8e84e68830..10cbd1fa9a0489 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query57.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query57.out
@@ -23,7 +23,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[item]
 --------------------------------PhysicalProject
-----------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))) and d_year IN (1998, 1999, 2000) and d_year IN (1998, 1999, 2000))
+----------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))))
 ------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[call_center]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query63.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query63.out
index 3bd844ce72c196..b16aa6edd4a56d 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query63.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query85.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query85.out
index 590589c61a42a0..0de3c1e87649c1 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query85.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query85.out
@@ -15,25 +15,24 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF7 ca_address_sk->[wr_refunded_addr_sk]
 ----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF4 cd_demo_sk->[wr_returning_cdemo_sk];RF5 cd_marital_status->[cd_marital_status];RF6 cd_education_status->[cd_education_status]
+------------------------------hashJoin[INNER_JOIN shuffle] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk) and (cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF4 cd_marital_status->[cd_marital_status];RF5 cd_education_status->[cd_education_status];RF6 cd_demo_sk->[wr_refunded_cdemo_sk]
 --------------------------------PhysicalProject
-----------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF3 cd_demo_sk->[wr_refunded_cdemo_sk]
+----------------------------------hashJoin[INNER_JOIN shuffle] hashCondition=((cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF3 cd_demo_sk->[wr_returning_cdemo_sk]
 ------------------------------------PhysicalProject
 --------------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=()
 ----------------------------------------PhysicalProject
 ------------------------------------------hashJoin[INNER_JOIN colocated] hashCondition=((web_sales.ws_item_sk = web_returns.wr_item_sk) and (web_sales.ws_order_number = web_returns.wr_order_number)) otherCondition=() build RFs:RF0 ws_item_sk->[wr_item_sk];RF1 ws_order_number->[wr_order_number]
 --------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF0 RF1 RF3 RF4 RF7
+----------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF0 RF1 RF3 RF6 RF7
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((web_sales.ws_net_profit <= 300.00) and (web_sales.ws_net_profit >= 50.00) and (web_sales.ws_sales_price <= 200.00) and (web_sales.ws_sales_price >= 50.00))
 ------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF8
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[web_page]
 ------------------------------------PhysicalProject
---------------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
-----------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6
+--------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF4 RF5
 --------------------------------PhysicalProject
-----------------------------------filter(cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
+----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ------------------------------------PhysicalOlapScan[customer_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('DE', 'FL', 'ID', 'IL', 'IN', 'MT', 'ND', 'OH', 'TX'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query88.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query88.out
index dc879d6daa5a4b..0bc35393abd55f 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query88.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query88.out
@@ -20,7 +20,7 @@ PhysicalResultSink
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF21 RF22 RF23
 ----------------------------------PhysicalProject
-------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalProject
 --------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
@@ -40,7 +40,7 @@ PhysicalResultSink
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF18 RF19 RF20
 ----------------------------------PhysicalProject
-------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalProject
 --------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
@@ -60,7 +60,7 @@ PhysicalResultSink
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[store_sales] apply RFs: RF15 RF16 RF17
 --------------------------------PhysicalProject
-----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------------PhysicalOlapScan[household_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
@@ -80,7 +80,7 @@ PhysicalResultSink
 ------------------------------PhysicalProject
 --------------------------------PhysicalOlapScan[store_sales] apply RFs: RF12 RF13 RF14
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
@@ -100,7 +100,7 @@ PhysicalResultSink
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store_sales] apply RFs: RF9 RF10 RF11
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
@@ -120,7 +120,7 @@ PhysicalResultSink
 --------------------------PhysicalProject
 ----------------------------PhysicalOlapScan[store_sales] apply RFs: RF6 RF7 RF8
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
@@ -140,7 +140,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[store_sales] apply RFs: RF3 RF4 RF5
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
@@ -160,7 +160,7 @@ PhysicalResultSink
 ----------------------PhysicalProject
 ------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query89.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query89.out
index c709c4df5fe097..e1c1fd9222d84f 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query89.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))) and i_category IN ('Electronics', 'Jewelry', 'Men', 'Music', 'Shoes', 'Women') and i_class IN ('accessories', 'athletic', 'maternity', 'portable', 'rock', 'semi-precious'))
+------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query91.out b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query91.out
index aa211a9f494891..6e532bb76fc3d7 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query91.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/noStatsRfPrune/query91.out
@@ -33,7 +33,7 @@ PhysicalResultSink
 ------------------------------filter((customer_address.ca_gmt_offset = -6.00))
 --------------------------------PhysicalOlapScan[customer_address]
 ------------------------PhysicalProject
---------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+--------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter((hd_buy_potential like '1001-5000%'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query13.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query13.out
index 61f8590deca15c..f6ffa6432e6645 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query13.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query13.out
@@ -9,7 +9,7 @@ PhysicalResultSink
 ------------PhysicalProject
 --------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('KS', 'MI', 'SD') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('CO', 'MO', 'ND') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00)))) OR (ca_state IN ('NH', 'OH', 'TX') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))))) build RFs:RF3 ca_address_sk->[ss_addr_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('M', 'S')) AND cd_education_status IN ('4 yr Degree', 'College')) AND ((cd_marital_status IN ('M', 'S') AND cd_education_status IN ('4 yr Degree', 'College')) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=() build RFs:RF1 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
@@ -20,7 +20,7 @@ PhysicalResultSink
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store]
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))) and cd_education_status IN ('4 yr Degree', 'College', 'Unknown') and cd_marital_status IN ('D', 'M', 'S'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter(hd_dep_count IN (1, 3))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query15.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query15.out
index 1fba646d62b40a..cbfedc9459a274 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query15.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query15.out
@@ -10,7 +10,7 @@ PhysicalResultSink
 --------------PhysicalProject
 ----------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[cs_sold_date_sk]
 ------------------PhysicalProject
---------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF1 ca_address_sk->[c_current_addr_sk]
+--------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer.c_current_addr_sk = customer_address.ca_address_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF1 ca_address_sk->[c_current_addr_sk]
 ----------------------PhysicalProject
 ------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=() build RFs:RF0 c_customer_sk->[cs_bill_customer_sk]
 --------------------------PhysicalProject
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query41.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query41.out
index ff811ef082cc23..34081b60b900b2 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query41.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('aquamarine', 'blue', 'chartreuse', 'chiffon', 'dodger', 'gainsboro', 'tan', 'violet') AND i_units IN ('Bunch', 'Dozen', 'Each', 'Ounce', 'Oz', 'Pound', 'Ton', 'Tsp')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'gainsboro')) AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('chiffon', 'violet')) AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('blue', 'chartreuse')) AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) AND i_size IN ('economy', 'medium'))))) OR ((i_color IN ('almond', 'blanched', 'indian', 'lime', 'peru', 'saddle', 'spring', 'tomato') AND i_units IN ('Box', 'Carton', 'Case', 'Dram', 'Gram', 'Pallet', 'Tbl', 'Unknown')) AND ((((((item.i_category = 'Women') AND i_color IN ('blanched', 'tomato')) AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('almond', 'lime')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('peru', 'saddle')) AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown')) AND i_size IN ('economy', 'medium')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'medium', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'medium') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) OR ((i_size IN ('economy', 'medium') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown'))) OR ((i_color IN ('blue', 'chartreuse') AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('peru', 'saddle') AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('aquamarine', 'gainsboro') AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((i_color IN ('chiffon', 'violet') AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR ((i_color IN ('blanched', 'tomato') AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium'))) OR ((i_color IN ('almond', 'lime') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query47.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query47.out
index b6f046eb01fe81..b27001e19a607d 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query47.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query47.out
@@ -23,7 +23,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[item]
 --------------------------------PhysicalProject
-----------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+----------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query48.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query48.out
index ed7ed3b4bdf669..283f05fff6d32c 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query48.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query48.out
@@ -18,7 +18,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[store]
 --------------------PhysicalProject
-----------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'U', 'W'))
+----------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 ------------------------PhysicalOlapScan[customer_demographics]
 ----------------PhysicalProject
 ------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query53.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query53.out
index 81e6091b663bf7..7dbd34d228fe3f 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query53.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query57.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query57.out
index 9b61dc54e2a91e..018e37ee77fbfa 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query57.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query57.out
@@ -23,7 +23,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[item]
 --------------------------------PhysicalProject
-----------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))) and d_year IN (1998, 1999, 2000) and d_year IN (1998, 1999, 2000))
+----------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))))
 ------------------------------------PhysicalOlapScan[date_dim]
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[call_center]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query63.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query63.out
index 2cd49bd8c40786..c5cea55eb7b009 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query63.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query85.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query85.out
index 08e59c1e36507e..54835db0dc8817 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query85.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query85.out
@@ -15,25 +15,24 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF7 ca_address_sk->[wr_refunded_addr_sk]
 ----------------------------PhysicalProject
-------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF4 cd_demo_sk->[wr_returning_cdemo_sk];RF5 cd_marital_status->[cd_marital_status];RF6 cd_education_status->[cd_education_status]
+------------------------------hashJoin[INNER_JOIN shuffle] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk) and (cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF4 cd_marital_status->[cd_marital_status];RF5 cd_education_status->[cd_education_status];RF6 cd_demo_sk->[wr_refunded_cdemo_sk]
 --------------------------------PhysicalProject
-----------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF3 cd_demo_sk->[wr_refunded_cdemo_sk]
+----------------------------------hashJoin[INNER_JOIN shuffle] hashCondition=((cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF3 cd_demo_sk->[wr_returning_cdemo_sk]
 ------------------------------------PhysicalProject
 --------------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF2 wp_web_page_sk->[ws_web_page_sk]
 ----------------------------------------PhysicalProject
 ------------------------------------------hashJoin[INNER_JOIN colocated] hashCondition=((web_sales.ws_item_sk = web_returns.wr_item_sk) and (web_sales.ws_order_number = web_returns.wr_order_number)) otherCondition=() build RFs:RF0 ws_item_sk->[wr_item_sk];RF1 ws_order_number->[wr_order_number]
 --------------------------------------------PhysicalProject
-----------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF0 RF1 RF3 RF4 RF7 RF9
+----------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF0 RF1 RF3 RF6 RF7 RF9
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((web_sales.ws_net_profit <= 300.00) and (web_sales.ws_net_profit >= 50.00) and (web_sales.ws_sales_price <= 200.00) and (web_sales.ws_sales_price >= 50.00))
 ------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF2 RF8
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[web_page]
 ------------------------------------PhysicalProject
---------------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
-----------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6
+--------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF4 RF5
 --------------------------------PhysicalProject
-----------------------------------filter(cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
+----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ------------------------------------PhysicalOlapScan[customer_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('DE', 'FL', 'ID', 'IL', 'IN', 'MT', 'ND', 'OH', 'TX'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query88.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query88.out
index dc879d6daa5a4b..0bc35393abd55f 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query88.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query88.out
@@ -20,7 +20,7 @@ PhysicalResultSink
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF21 RF22 RF23
 ----------------------------------PhysicalProject
-------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalProject
 --------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
@@ -40,7 +40,7 @@ PhysicalResultSink
 ----------------------------------PhysicalProject
 ------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF18 RF19 RF20
 ----------------------------------PhysicalProject
-------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------------PhysicalOlapScan[household_demographics]
 ------------------------------PhysicalProject
 --------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
@@ -60,7 +60,7 @@ PhysicalResultSink
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[store_sales] apply RFs: RF15 RF16 RF17
 --------------------------------PhysicalProject
-----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------------PhysicalOlapScan[household_demographics]
 ----------------------------PhysicalProject
 ------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
@@ -80,7 +80,7 @@ PhysicalResultSink
 ------------------------------PhysicalProject
 --------------------------------PhysicalOlapScan[store_sales] apply RFs: RF12 RF13 RF14
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
@@ -100,7 +100,7 @@ PhysicalResultSink
 ----------------------------PhysicalProject
 ------------------------------PhysicalOlapScan[store_sales] apply RFs: RF9 RF10 RF11
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
@@ -120,7 +120,7 @@ PhysicalResultSink
 --------------------------PhysicalProject
 ----------------------------PhysicalOlapScan[store_sales] apply RFs: RF6 RF7 RF8
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
@@ -140,7 +140,7 @@ PhysicalResultSink
 ------------------------PhysicalProject
 --------------------------PhysicalOlapScan[store_sales] apply RFs: RF3 RF4 RF5
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
@@ -160,7 +160,7 @@ PhysicalResultSink
 ----------------------PhysicalProject
 ------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query89.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query89.out
index 661b47d0ea980a..35a90cb94290b7 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query89.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))) and i_category IN ('Electronics', 'Jewelry', 'Men', 'Music', 'Shoes', 'Women') and i_class IN ('accessories', 'athletic', 'maternity', 'portable', 'rock', 'semi-precious'))
+------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query91.out b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query91.out
index c19b43be01a9df..d165c286c01e50 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query91.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/no_stats_shape/query91.out
@@ -33,7 +33,7 @@ PhysicalResultSink
 ------------------------------filter((customer_address.ca_gmt_offset = -6.00))
 --------------------------------PhysicalOlapScan[customer_address]
 ------------------------PhysicalProject
---------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+--------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
 ----------------------filter((hd_buy_potential like '1001-5000%'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query13.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query13.out
index f3c8db3bfc436d..1210eca43f9d3f 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query13.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query13.out
@@ -7,9 +7,9 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=()
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('M', 'S')) AND cd_education_status IN ('4 yr Degree', 'College')) AND ((cd_marital_status IN ('M', 'S') AND cd_education_status IN ('4 yr Degree', 'College')) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
+--------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
 ----------------PhysicalProject
-------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))) and cd_education_status IN ('4 yr Degree', 'College', 'Unknown') and cd_marital_status IN ('D', 'M', 'S'))
+------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
 --------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=() build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query15.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query15.out
index f15477f65e12fb..93b2d0cee9c5d7 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query15.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query15.out
@@ -8,7 +8,7 @@ PhysicalResultSink
 ----------PhysicalDistribute[DistributionSpecHash]
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00)))
+----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00)))
 ------------------PhysicalProject
 --------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[cs_sold_date_sk]
 ----------------------PhysicalProject
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query41.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query41.out
index ff811ef082cc23..34081b60b900b2 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query41.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('aquamarine', 'blue', 'chartreuse', 'chiffon', 'dodger', 'gainsboro', 'tan', 'violet') AND i_units IN ('Bunch', 'Dozen', 'Each', 'Ounce', 'Oz', 'Pound', 'Ton', 'Tsp')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'gainsboro')) AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('chiffon', 'violet')) AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('blue', 'chartreuse')) AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) AND i_size IN ('economy', 'medium'))))) OR ((i_color IN ('almond', 'blanched', 'indian', 'lime', 'peru', 'saddle', 'spring', 'tomato') AND i_units IN ('Box', 'Carton', 'Case', 'Dram', 'Gram', 'Pallet', 'Tbl', 'Unknown')) AND ((((((item.i_category = 'Women') AND i_color IN ('blanched', 'tomato')) AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('almond', 'lime')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('peru', 'saddle')) AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown')) AND i_size IN ('economy', 'medium')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'medium', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'medium') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) OR ((i_size IN ('economy', 'medium') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown'))) OR ((i_color IN ('blue', 'chartreuse') AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('peru', 'saddle') AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('aquamarine', 'gainsboro') AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((i_color IN ('chiffon', 'violet') AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR ((i_color IN ('blanched', 'tomato') AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium'))) OR ((i_color IN ('almond', 'lime') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query47.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query47.out
index e115c8751281e0..52bd4fa6fbf623 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query47.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query47.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+--------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[item]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query48.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query48.out
index 476aa9dd8793af..89ce4eb76395d6 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query48.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query48.out
@@ -7,23 +7,23 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=()
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
+--------------hashJoin[INNER_JOIN shuffleBucket] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF2 ca_address_sk->[ss_addr_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF1 ca_address_sk->[ss_addr_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
 --------------------------filter((store_sales.ss_net_profit <= 25000.00) and (store_sales.ss_net_profit >= 0.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
 ----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'U', 'W'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
-----------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
-------------------------PhysicalOlapScan[customer_address]
+----------------------filter((date_dim.d_year = 1999))
+------------------------PhysicalOlapScan[date_dim]
 ----------------PhysicalProject
-------------------filter((date_dim.d_year = 1999))
---------------------PhysicalOlapScan[date_dim]
+------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
+--------------------PhysicalOlapScan[customer_address]
 ------------PhysicalProject
 --------------PhysicalOlapScan[store]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query53.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query53.out
index 93289fca48e4ef..d14fe74213eb0d 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query53.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query57.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query57.out
index 053e8bfc4c7f54..60276268fc3224 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query57.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query57.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[catalog_sales] apply RFs: RF0
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))) and d_year IN (1998, 1999, 2000) and d_year IN (1998, 1999, 2000))
+--------------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[item]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query63.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query63.out
index 3bd844ce72c196..b16aa6edd4a56d 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query63.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query85.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query85.out
index c428ce03bde80e..a2183ccaa646ca 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query85.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query85.out
@@ -9,18 +9,17 @@ PhysicalResultSink
 ------------PhysicalDistribute[DistributionSpecHash]
 --------------hashAgg[LOCAL]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=()
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=()
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=()
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF6 wr_returning_cdemo_sk->[cd_demo_sk];RF7 cd_marital_status->[cd_marital_status];RF8 cd_education_status->[cd_education_status]
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF5 wr_returning_cdemo_sk->[cd_demo_sk];RF6 cd_marital_status->[cd_marital_status];RF7 cd_education_status->[cd_education_status]
-----------------------------PhysicalProject
-------------------------------filter(cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
---------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6 RF7
+--------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF6 RF7 RF8
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=()
 ----------------------------PhysicalProject
 ------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF4 wr_refunded_cdemo_sk->[cd_demo_sk]
 --------------------------------PhysicalProject
-----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
+----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF4
 --------------------------------PhysicalProject
 ----------------------------------hashJoin[INNER_JOIN shuffleBucket] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF3 ca_address_sk->[wr_refunded_addr_sk]
@@ -39,8 +38,8 @@ PhysicalResultSink
 ------------------------------------PhysicalProject
 --------------------------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('DE', 'FL', 'ID', 'IL', 'IN', 'MT', 'ND', 'OH', 'TX'))
 ----------------------------------------PhysicalOlapScan[customer_address]
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[reason]
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[web_page]
 --------------------PhysicalProject
-----------------------PhysicalOlapScan[web_page]
+----------------------PhysicalOlapScan[reason]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query88.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query88.out
index bca8b0d069014b..af35685d6e46ac 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query88.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query88.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -43,7 +43,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -63,7 +63,7 @@ PhysicalResultSink
 ----------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
 ------------------------------------PhysicalOlapScan[time_dim]
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((store.s_store_name = 'ese'))
@@ -83,7 +83,7 @@ PhysicalResultSink
 --------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
 ----------------------------------PhysicalOlapScan[time_dim]
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((store.s_store_name = 'ese'))
@@ -103,7 +103,7 @@ PhysicalResultSink
 ------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
 --------------------------------PhysicalOlapScan[time_dim]
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((store.s_store_name = 'ese'))
@@ -123,7 +123,7 @@ PhysicalResultSink
 ----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
 ------------------------------PhysicalOlapScan[time_dim]
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((store.s_store_name = 'ese'))
@@ -143,7 +143,7 @@ PhysicalResultSink
 --------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
 ----------------------------PhysicalOlapScan[time_dim]
 --------------------PhysicalProject
-----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------PhysicalOlapScan[household_demographics]
 ----------------PhysicalProject
 ------------------filter((store.s_store_name = 'ese'))
@@ -163,7 +163,7 @@ PhysicalResultSink
 ------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
 --------------------------PhysicalOlapScan[time_dim]
 ------------------PhysicalProject
---------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------PhysicalOlapScan[household_demographics]
 --------------PhysicalProject
 ----------------filter((store.s_store_name = 'ese'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query89.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query89.out
index c709c4df5fe097..e1c1fd9222d84f 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query89.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))) and i_category IN ('Electronics', 'Jewelry', 'Men', 'Music', 'Shoes', 'Women') and i_class IN ('accessories', 'athletic', 'maternity', 'portable', 'rock', 'semi-precious'))
+------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query91.out b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query91.out
index e2a4ed89af442d..2788bd2d8cff0c 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query91.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/rf_prune/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like '1001-5000%'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query13.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query13.out
index 17cd82b3e1cf75..357029ffd2214f 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query13.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query13.out
@@ -7,9 +7,9 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=() build RFs:RF4 s_store_sk->[ss_store_sk]
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('M', 'S')) AND cd_education_status IN ('4 yr Degree', 'College')) AND ((cd_marital_status IN ('M', 'S') AND cd_education_status IN ('4 yr Degree', 'College')) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
+--------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
 ----------------PhysicalProject
-------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))) and cd_education_status IN ('4 yr Degree', 'College', 'Unknown') and cd_marital_status IN ('D', 'M', 'S'))
+------------------filter(((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '4 yr Degree'))))
 --------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=() build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query15.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query15.out
index b80017b7ebd0f9..f617754de74f6b 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query15.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query15.out
@@ -8,7 +8,7 @@ PhysicalResultSink
 ----------PhysicalDistribute[DistributionSpecHash]
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
+----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
 ------------------PhysicalProject
 --------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[cs_sold_date_sk]
 ----------------------PhysicalProject
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query41.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query41.out
index ff811ef082cc23..34081b60b900b2 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query41.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('aquamarine', 'blue', 'chartreuse', 'chiffon', 'dodger', 'gainsboro', 'tan', 'violet') AND i_units IN ('Bunch', 'Dozen', 'Each', 'Ounce', 'Oz', 'Pound', 'Ton', 'Tsp')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'gainsboro')) AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('chiffon', 'violet')) AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('blue', 'chartreuse')) AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) AND i_size IN ('economy', 'medium'))))) OR ((i_color IN ('almond', 'blanched', 'indian', 'lime', 'peru', 'saddle', 'spring', 'tomato') AND i_units IN ('Box', 'Carton', 'Case', 'Dram', 'Gram', 'Pallet', 'Tbl', 'Unknown')) AND ((((((item.i_category = 'Women') AND i_color IN ('blanched', 'tomato')) AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium')) OR ((((item.i_category = 'Women') AND i_color IN ('almond', 'lime')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))) OR (((((item.i_category = 'Men') AND i_color IN ('peru', 'saddle')) AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown')) AND i_size IN ('economy', 'medium')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'medium', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'medium') AND i_color IN ('dodger', 'tan')) AND i_units IN ('Bunch', 'Tsp')) OR ((i_size IN ('economy', 'medium') AND i_color IN ('indian', 'spring')) AND i_units IN ('Carton', 'Unknown'))) OR ((i_color IN ('blue', 'chartreuse') AND i_units IN ('Each', 'Oz')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('peru', 'saddle') AND i_units IN ('Gram', 'Pallet')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('aquamarine', 'gainsboro') AND i_units IN ('Dozen', 'Ounce')) AND i_size IN ('economy', 'medium')) OR ((i_color IN ('chiffon', 'violet') AND i_units IN ('Pound', 'Ton')) AND i_size IN ('extra large', 'small'))) OR ((i_color IN ('blanched', 'tomato') AND i_units IN ('Case', 'Tbl')) AND i_size IN ('economy', 'medium'))) OR ((i_color IN ('almond', 'lime') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'small'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query47.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query47.out
index 7a668b06c433e5..f33181c085733c 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query47.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query47.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+--------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[item]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query48.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query48.out
index c81868cacca7a6..8bb4cfa24cd5f9 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query48.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query48.out
@@ -7,23 +7,23 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=() build RFs:RF3 s_store_sk->[ss_store_sk]
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
+--------------hashJoin[INNER_JOIN shuffleBucket] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF2 ca_address_sk->[ss_addr_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IA', 'MD', 'MN') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('IL', 'TX', 'VA') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('IN', 'MI', 'WI') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF1 ca_address_sk->[ss_addr_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
 --------------------------filter((store_sales.ss_net_profit <= 25000.00) and (store_sales.ss_net_profit >= 0.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
 ----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF3
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'U', 'W'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'U') AND (customer_demographics.cd_education_status = 'Primary')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'College'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
-----------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
-------------------------PhysicalOlapScan[customer_address]
+----------------------filter((date_dim.d_year = 1999))
+------------------------PhysicalOlapScan[date_dim]
 ----------------PhysicalProject
-------------------filter((date_dim.d_year = 1999))
---------------------PhysicalOlapScan[date_dim]
+------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('IA', 'IL', 'IN', 'MD', 'MI', 'MN', 'TX', 'VA', 'WI'))
+--------------------PhysicalOlapScan[customer_address]
 ------------PhysicalProject
 --------------PhysicalOlapScan[store]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query53.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query53.out
index 81e6091b663bf7..7dbd34d228fe3f 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query53.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query57.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query57.out
index 7bbcf019701d4d..15dda452ebc984 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query57.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query57.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[catalog_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))) and d_year IN (1998, 1999, 2000) and d_year IN (1998, 1999, 2000))
+--------------------------------------filter((((date_dim.d_year = 1999) OR ((date_dim.d_year = 1998) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[item]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query63.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query63.out
index 2cd49bd8c40786..c5cea55eb7b009 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query63.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query85.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query85.out
index c69ca3b6c0ed48..f922c1edf94241 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query85.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query85.out
@@ -9,38 +9,37 @@ PhysicalResultSink
 ------------PhysicalDistribute[DistributionSpecHash]
 --------------hashAgg[LOCAL]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF9 wp_web_page_sk->[ws_web_page_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=() build RFs:RF9 r_reason_sk->[wr_reason_sk]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=() build RFs:RF8 r_reason_sk->[wr_reason_sk]
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF6 wr_returning_cdemo_sk->[cd_demo_sk];RF7 cd_marital_status->[cd_marital_status];RF8 cd_education_status->[cd_education_status]
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF5 wr_returning_cdemo_sk->[cd_demo_sk];RF6 cd_marital_status->[cd_marital_status];RF7 cd_education_status->[cd_education_status]
-----------------------------PhysicalProject
-------------------------------filter(cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
---------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6 RF7
+--------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF6 RF7 RF8
+------------------------PhysicalProject
+--------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF5 wp_web_page_sk->[ws_web_page_sk]
 ----------------------------PhysicalProject
 ------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_demo_sk = web_returns.wr_refunded_cdemo_sk)) otherCondition=((((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) AND ((web_sales.ws_sales_price >= 100.00) AND (web_sales.ws_sales_price <= 150.00))) OR (((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary')) AND ((web_sales.ws_sales_price >= 50.00) AND (web_sales.ws_sales_price <= 100.00)))) OR (((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree')) AND ((web_sales.ws_sales_price >= 150.00) AND (web_sales.ws_sales_price <= 200.00))))) build RFs:RF4 wr_refunded_cdemo_sk->[cd_demo_sk]
 --------------------------------PhysicalProject
-----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('4 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('M', 'S', 'W'))
+----------------------------------filter(((((cd1.cd_marital_status = 'M') AND (cd1.cd_education_status = '4 yr Degree')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'Secondary'))) OR ((cd1.cd_marital_status = 'W') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF4
 --------------------------------PhysicalProject
 ----------------------------------hashJoin[INNER_JOIN shuffleBucket] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('DE', 'FL', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('ID', 'IN', 'ND') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('IL', 'MT', 'OH') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF3 ca_address_sk->[wr_refunded_addr_sk]
 ------------------------------------PhysicalProject
 --------------------------------------hashJoin[INNER_JOIN colocated] hashCondition=((web_sales.ws_item_sk = web_returns.wr_item_sk) and (web_sales.ws_order_number = web_returns.wr_order_number)) otherCondition=() build RFs:RF1 ws_item_sk->[wr_item_sk];RF2 ws_order_number->[wr_order_number]
 ----------------------------------------PhysicalProject
-------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF1 RF2 RF3 RF8
+------------------------------------------PhysicalOlapScan[web_returns] apply RFs: RF1 RF2 RF3 RF9
 ----------------------------------------PhysicalProject
 ------------------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF0 d_date_sk->[ws_sold_date_sk]
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((web_sales.ws_net_profit <= 300.00) and (web_sales.ws_net_profit >= 50.00) and (web_sales.ws_sales_price <= 200.00) and (web_sales.ws_sales_price >= 50.00))
-------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF0 RF9
+------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF0 RF5
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((date_dim.d_year = 2000))
 ------------------------------------------------PhysicalOlapScan[date_dim]
 ------------------------------------PhysicalProject
 --------------------------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('DE', 'FL', 'ID', 'IL', 'IN', 'MT', 'ND', 'OH', 'TX'))
 ----------------------------------------PhysicalOlapScan[customer_address]
-------------------------PhysicalProject
---------------------------PhysicalOlapScan[reason]
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[web_page]
 --------------------PhysicalProject
-----------------------PhysicalOlapScan[web_page]
+----------------------PhysicalOlapScan[reason]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query88.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query88.out
index bca8b0d069014b..af35685d6e46ac 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query88.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query88.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -43,7 +43,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -63,7 +63,7 @@ PhysicalResultSink
 ----------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
 ------------------------------------PhysicalOlapScan[time_dim]
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((store.s_store_name = 'ese'))
@@ -83,7 +83,7 @@ PhysicalResultSink
 --------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
 ----------------------------------PhysicalOlapScan[time_dim]
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((store.s_store_name = 'ese'))
@@ -103,7 +103,7 @@ PhysicalResultSink
 ------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
 --------------------------------PhysicalOlapScan[time_dim]
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((store.s_store_name = 'ese'))
@@ -123,7 +123,7 @@ PhysicalResultSink
 ----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
 ------------------------------PhysicalOlapScan[time_dim]
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+------------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((store.s_store_name = 'ese'))
@@ -143,7 +143,7 @@ PhysicalResultSink
 --------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
 ----------------------------PhysicalOlapScan[time_dim]
 --------------------PhysicalProject
-----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+----------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------PhysicalOlapScan[household_demographics]
 ----------------PhysicalProject
 ------------------filter((store.s_store_name = 'ese'))
@@ -163,7 +163,7 @@ PhysicalResultSink
 ------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
 --------------------------PhysicalOlapScan[time_dim]
 ------------------PhysicalProject
---------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 3, 4))
+--------------------filter(((((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1)) OR ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= 6))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------PhysicalOlapScan[household_demographics]
 --------------PhysicalProject
 ----------------filter((store.s_store_name = 'ese'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query89.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query89.out
index 661b47d0ea980a..35a90cb94290b7 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query89.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))) and i_category IN ('Electronics', 'Jewelry', 'Men', 'Music', 'Shoes', 'Women') and i_class IN ('accessories', 'athletic', 'maternity', 'portable', 'rock', 'semi-precious'))
+------------------------------------------filter(((i_category IN ('Electronics', 'Jewelry', 'Shoes') AND i_class IN ('athletic', 'portable', 'semi-precious')) OR (i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'maternity', 'rock'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 1999))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query91.out b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query91.out
index 6f3970cbb29d50..ca8fac70d693aa 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query91.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf100/shape/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like '1001-5000%'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/bs_downgrade_shape/query13.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/bs_downgrade_shape/query13.out
index 30208c887cae7a..c0aecbb0023f41 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/bs_downgrade_shape/query13.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/bs_downgrade_shape/query13.out
@@ -14,14 +14,14 @@ PhysicalResultSink
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('D', 'W')) AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((cd_marital_status IN ('D', 'W') AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF1 hd_demo_sk->[ss_hdemo_sk]
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF1 hd_demo_sk->[ss_hdemo_sk]
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=() build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ----------------------------PhysicalProject
 ------------------------------filter((store_sales.ss_net_profit <= 300.00) and (store_sales.ss_net_profit >= 50.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
 --------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF4
 ----------------------------PhysicalProject
-------------------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'M', 'W'))
+------------------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 --------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------PhysicalProject
 --------------------------filter(hd_dep_count IN (1, 3))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/bs_downgrade_shape/query91.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/bs_downgrade_shape/query91.out
index 624685e9dab961..69fe2228399236 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/bs_downgrade_shape/query91.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/bs_downgrade_shape/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like 'Unknown%'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query13.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query13.out
index 30208c887cae7a..c0aecbb0023f41 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query13.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query13.out
@@ -14,14 +14,14 @@ PhysicalResultSink
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((((household_demographics.hd_dep_count = 1) AND cd_marital_status IN ('D', 'W')) AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((cd_marital_status IN ('D', 'W') AND cd_education_status IN ('2 yr Degree', 'Primary')) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00)))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF1 hd_demo_sk->[ss_hdemo_sk]
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=((((household_demographics.hd_dep_count = 1) AND ((((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR (((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) OR ((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) AND (household_demographics.hd_dep_count = 3)))) build RFs:RF1 hd_demo_sk->[ss_hdemo_sk]
 ------------------------PhysicalProject
 --------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=() build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ----------------------------PhysicalProject
 ------------------------------filter((store_sales.ss_net_profit <= 300.00) and (store_sales.ss_net_profit >= 50.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
 --------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF4
 ----------------------------PhysicalProject
-------------------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))) and cd_education_status IN ('2 yr Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'M', 'W'))
+------------------------------filter(((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'College')) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Primary'))) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = '2 yr Degree'))))
 --------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------PhysicalProject
 --------------------------filter(hd_dep_count IN (1, 3))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query15.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query15.out
index 6f522756f18098..3e0b283a513dd2 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query15.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query15.out
@@ -8,7 +8,7 @@ PhysicalResultSink
 ----------PhysicalDistribute[DistributionSpecHash]
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274') OR ca_state IN ('CA', 'GA', 'WA')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
+----------------hashJoin[INNER_JOIN shuffle] hashCondition=((catalog_sales.cs_bill_customer_sk = customer.c_customer_sk)) otherCondition=(((ca_state IN ('CA', 'GA', 'WA') OR substring(ca_zip, 1, 5) IN ('80348', '81792', '83405', '85392', '85460', '85669', '86197', '86475', '88274')) OR (catalog_sales.cs_sales_price > 500.00))) build RFs:RF2 c_customer_sk->[cs_bill_customer_sk]
 ------------------PhysicalProject
 --------------------hashJoin[INNER_JOIN broadcast] hashCondition=((catalog_sales.cs_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[cs_sold_date_sk]
 ----------------------PhysicalProject
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query41.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query41.out
index c870e728a39819..c27e19cc9f2387 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query41.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query41.out
@@ -18,6 +18,6 @@ PhysicalResultSink
 ------------------------PhysicalDistribute[DistributionSpecHash]
 --------------------------hashAgg[LOCAL]
 ----------------------------PhysicalProject
-------------------------------filter((((i_color IN ('forest', 'lime', 'maroon', 'navy', 'powder', 'sky', 'slate', 'smoke') AND i_units IN ('Bunch', 'Case', 'Dozen', 'Gross', 'Lb', 'Ounce', 'Pallet', 'Pound')) AND ((((((item.i_category = 'Women') AND i_color IN ('forest', 'lime')) AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('navy', 'slate')) AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('powder', 'sky')) AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) AND i_size IN ('economy', 'small'))))) OR ((i_color IN ('aquamarine', 'dark', 'firebrick', 'frosted', 'papaya', 'peach', 'plum', 'sienna') AND i_units IN ('Box', 'Bundle', 'Carton', 'Cup', 'Dram', 'Each', 'Tbl', 'Ton')) AND ((((((item.i_category = 'Women') AND i_color IN ('aquamarine', 'dark')) AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small')) OR ((((item.i_category = 'Women') AND i_color IN ('frosted', 'plum')) AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))) OR (((((item.i_category = 'Men') AND i_color IN ('papaya', 'peach')) AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large')) OR ((((item.i_category = 'Men') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each')) AND i_size IN ('economy', 'small')))))) and i_category IN ('Men', 'Women') and i_size IN ('N/A', 'economy', 'extra large', 'large', 'petite', 'small'))
+------------------------------filter((((item.i_category = 'Men') AND (((((i_size IN ('economy', 'small') AND i_color IN ('maroon', 'smoke')) AND i_units IN ('Case', 'Ounce')) OR ((i_size IN ('economy', 'small') AND i_color IN ('firebrick', 'sienna')) AND i_units IN ('Cup', 'Each'))) OR ((i_color IN ('powder', 'sky') AND i_units IN ('Dozen', 'Lb')) AND i_size IN ('N/A', 'large'))) OR ((i_color IN ('papaya', 'peach') AND i_units IN ('Bundle', 'Carton')) AND i_size IN ('N/A', 'large')))) OR ((item.i_category = 'Women') AND (((((i_color IN ('forest', 'lime') AND i_units IN ('Pallet', 'Pound')) AND i_size IN ('economy', 'small')) OR ((i_color IN ('navy', 'slate') AND i_units IN ('Bunch', 'Gross')) AND i_size IN ('extra large', 'petite'))) OR ((i_color IN ('aquamarine', 'dark') AND i_units IN ('Tbl', 'Ton')) AND i_size IN ('economy', 'small'))) OR ((i_color IN ('frosted', 'plum') AND i_units IN ('Box', 'Dram')) AND i_size IN ('extra large', 'petite'))))))
 --------------------------------PhysicalOlapScan[item]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query47.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query47.out
index caec3b20581ed5..0ea84e3ca2b33d 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query47.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query47.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))) and d_year IN (1999, 2000, 2001) and d_year IN (1999, 2000, 2001))
+--------------------------------------filter((((date_dim.d_year = 2000) OR ((date_dim.d_year = 1999) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2001) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[store]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query48.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query48.out
index 3fcfef0d8f68ba..086a41be4265ed 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query48.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query48.out
@@ -7,23 +7,23 @@ PhysicalResultSink
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN broadcast] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=() build RFs:RF3 s_store_sk->[ss_store_sk]
 ------------PhysicalProject
---------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF2 d_date_sk->[ss_sold_date_sk]
+--------------hashJoin[INNER_JOIN shuffleBucket] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('ND', 'NY', 'SD') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('GA', 'KS', 'MD') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('CO', 'MN', 'NC') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF2 ca_address_sk->[ss_addr_sk]
 ----------------PhysicalProject
-------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('ND', 'NY', 'SD') AND ((store_sales.ss_net_profit >= 0.00) AND (store_sales.ss_net_profit <= 2000.00))) OR (ca_state IN ('GA', 'KS', 'MD') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 3000.00)))) OR (ca_state IN ('CO', 'MN', 'NC') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 25000.00))))) build RFs:RF1 ca_address_sk->[ss_addr_sk]
+------------------hashJoin[INNER_JOIN broadcast] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[ss_sold_date_sk]
 --------------------PhysicalProject
 ----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=((((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'Secondary')) AND ((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00))) OR (((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '2 yr Degree')) AND ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00)))) OR (((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Advanced Degree')) AND ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))) build RFs:RF0 cd_demo_sk->[ss_cdemo_sk]
 ------------------------PhysicalProject
 --------------------------filter((store_sales.ss_net_profit <= 25000.00) and (store_sales.ss_net_profit >= 0.00) and (store_sales.ss_sales_price <= 200.00) and (store_sales.ss_sales_price >= 50.00))
 ----------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF3
 ------------------------PhysicalProject
---------------------------filter(((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'Secondary')) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '2 yr Degree'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('2 yr Degree', 'Advanced Degree', 'Secondary') and cd_marital_status IN ('D', 'M', 'S'))
+--------------------------filter(((((customer_demographics.cd_marital_status = 'S') AND (customer_demographics.cd_education_status = 'Secondary')) OR ((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = '2 yr Degree'))) OR ((customer_demographics.cd_marital_status = 'D') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 ----------------------------PhysicalOlapScan[customer_demographics]
 --------------------PhysicalProject
-----------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('CO', 'GA', 'KS', 'MD', 'MN', 'NC', 'ND', 'NY', 'SD'))
-------------------------PhysicalOlapScan[customer_address]
+----------------------filter((date_dim.d_year = 2001))
+------------------------PhysicalOlapScan[date_dim]
 ----------------PhysicalProject
-------------------filter((date_dim.d_year = 2001))
---------------------PhysicalOlapScan[date_dim]
+------------------filter((customer_address.ca_country = 'United States') and ca_state IN ('CO', 'GA', 'KS', 'MD', 'MN', 'NC', 'ND', 'NY', 'SD'))
+--------------------PhysicalOlapScan[customer_address]
 ------------PhysicalProject
 --------------PhysicalOlapScan[store]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query53.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query53.out
index 07d64a35b071ca..fe473000e5966d 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query53.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query53.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query57.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query57.out
index c1b802ebfc4498..356837343861e9 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query57.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query57.out
@@ -21,7 +21,7 @@ PhysicalCteAnchor ( cteId=CTEId#0 )
 ------------------------------------PhysicalProject
 --------------------------------------PhysicalOlapScan[catalog_sales] apply RFs: RF0 RF1 RF2
 ------------------------------------PhysicalProject
---------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))) and d_year IN (2000, 2001, 2002))
+--------------------------------------filter((((date_dim.d_year = 2001) OR ((date_dim.d_year = 2000) AND (date_dim.d_moy = 12))) OR ((date_dim.d_year = 2002) AND (date_dim.d_moy = 1))))
 ----------------------------------------PhysicalOlapScan[date_dim]
 --------------------------------PhysicalProject
 ----------------------------------PhysicalOlapScan[call_center]
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query63.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query63.out
index d1807a29db2f0d..8452d151a7d207 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query63.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query63.out
@@ -22,7 +22,7 @@ PhysicalResultSink
 --------------------------------------PhysicalProject
 ----------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 --------------------------------------PhysicalProject
-----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))) and i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'exportiunivamalg #9', 'importoamalg #1', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9') and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Music', 'Women') and i_class IN ('accessories', 'classical', 'fragrances', 'pants', 'personal', 'portable', 'reference', 'self-help'))
+----------------------------------------filter((((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('personal', 'portable', 'reference', 'self-help')) AND i_brand IN ('exportiunivamalg #9', 'scholaramalgamalg #14', 'scholaramalgamalg #7', 'scholaramalgamalg #9')) OR ((i_category IN ('Men', 'Music', 'Women') AND i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1'))))
 ------------------------------------------PhysicalOlapScan[item]
 ----------------------------------PhysicalProject
 ------------------------------------filter(d_month_seq IN (1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query85.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query85.out
index 1781cd24d5b9f5..1ad51b4c22aa79 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query85.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query85.out
@@ -11,12 +11,13 @@ PhysicalResultSink
 ----------------PhysicalProject
 ------------------hashJoin[INNER_JOIN broadcast] hashCondition=((reason.r_reason_sk = web_returns.wr_reason_sk)) otherCondition=() build RFs:RF9 r_reason_sk->[wr_reason_sk]
 --------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF6 wr_returning_cdemo_sk->[cd_demo_sk];RF7 cd_marital_status->[cd_marital_status];RF8 cd_education_status->[cd_education_status]
+----------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF8 ws_web_page_sk->[wp_web_page_sk]
 ------------------------PhysicalProject
---------------------------filter(cd_education_status IN ('Advanced Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'S', 'U'))
-----------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF6 RF7 RF8
+--------------------------PhysicalOlapScan[web_page] apply RFs: RF8
 ------------------------PhysicalProject
---------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_web_page_sk = web_page.wp_web_page_sk)) otherCondition=() build RFs:RF5 wp_web_page_sk->[ws_web_page_sk]
+--------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((cd1.cd_education_status = cd2.cd_education_status) and (cd1.cd_marital_status = cd2.cd_marital_status) and (cd2.cd_demo_sk = web_returns.wr_returning_cdemo_sk)) otherCondition=() build RFs:RF5 wr_returning_cdemo_sk->[cd_demo_sk];RF6 cd_marital_status->[cd_marital_status];RF7 cd_education_status->[cd_education_status]
+----------------------------PhysicalProject
+------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF5 RF6 RF7
 ----------------------------PhysicalProject
 ------------------------------hashJoin[INNER_JOIN bucketShuffle] hashCondition=((customer_address.ca_address_sk = web_returns.wr_refunded_addr_sk)) otherCondition=((((ca_state IN ('IA', 'NC', 'TX') AND ((web_sales.ws_net_profit >= 100.00) AND (web_sales.ws_net_profit <= 200.00))) OR (ca_state IN ('GA', 'WI', 'WV') AND ((web_sales.ws_net_profit >= 150.00) AND (web_sales.ws_net_profit <= 300.00)))) OR (ca_state IN ('KY', 'OK', 'VA') AND ((web_sales.ws_net_profit >= 50.00) AND (web_sales.ws_net_profit <= 250.00))))) build RFs:RF4 wr_refunded_addr_sk->[ca_address_sk]
 --------------------------------PhysicalProject
@@ -32,15 +33,13 @@ PhysicalResultSink
 ------------------------------------------hashJoin[INNER_JOIN broadcast] hashCondition=((web_sales.ws_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF0 d_date_sk->[ws_sold_date_sk]
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((web_sales.ws_net_profit <= 300.00) and (web_sales.ws_net_profit >= 50.00) and (web_sales.ws_sales_price <= 200.00) and (web_sales.ws_sales_price >= 50.00))
-------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF0 RF5
+------------------------------------------------PhysicalOlapScan[web_sales] apply RFs: RF0
 --------------------------------------------PhysicalProject
 ----------------------------------------------filter((date_dim.d_year = 1998))
 ------------------------------------------------PhysicalOlapScan[date_dim]
 ------------------------------------PhysicalProject
---------------------------------------filter(((((cd1.cd_marital_status = 'D') AND (cd1.cd_education_status = 'Primary')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'College'))) OR ((cd1.cd_marital_status = 'U') AND (cd1.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'College', 'Primary') and cd_marital_status IN ('D', 'S', 'U'))
+--------------------------------------filter(((((cd1.cd_marital_status = 'D') AND (cd1.cd_education_status = 'Primary')) OR ((cd1.cd_marital_status = 'S') AND (cd1.cd_education_status = 'College'))) OR ((cd1.cd_marital_status = 'U') AND (cd1.cd_education_status = 'Advanced Degree'))))
 ----------------------------------------PhysicalOlapScan[customer_demographics]
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[web_page]
 --------------------PhysicalProject
 ----------------------PhysicalOlapScan[reason]
 
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query88.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query88.out
index dc3f1ece14f64d..c1d5cc7801f9ef 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query88.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query88.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 8) and (time_dim.t_minute >= 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -43,7 +43,7 @@ PhysicalResultSink
 ------------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute < 30))
 --------------------------------------PhysicalOlapScan[time_dim]
 ------------------------------PhysicalProject
---------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------------PhysicalOlapScan[household_demographics]
 --------------------------PhysicalProject
 ----------------------------filter((store.s_store_name = 'ese'))
@@ -63,7 +63,7 @@ PhysicalResultSink
 ----------------------------------filter((time_dim.t_hour = 9) and (time_dim.t_minute >= 30))
 ------------------------------------PhysicalOlapScan[time_dim]
 ----------------------------PhysicalProject
-------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+------------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------------PhysicalOlapScan[household_demographics]
 ------------------------PhysicalProject
 --------------------------filter((store.s_store_name = 'ese'))
@@ -83,7 +83,7 @@ PhysicalResultSink
 --------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute < 30))
 ----------------------------------PhysicalOlapScan[time_dim]
 --------------------------PhysicalProject
-----------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+----------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------------PhysicalOlapScan[household_demographics]
 ----------------------PhysicalProject
 ------------------------filter((store.s_store_name = 'ese'))
@@ -103,7 +103,7 @@ PhysicalResultSink
 ------------------------------filter((time_dim.t_hour = 10) and (time_dim.t_minute >= 30))
 --------------------------------PhysicalOlapScan[time_dim]
 ------------------------PhysicalProject
---------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------------PhysicalOlapScan[household_demographics]
 --------------------PhysicalProject
 ----------------------filter((store.s_store_name = 'ese'))
@@ -123,7 +123,7 @@ PhysicalResultSink
 ----------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute < 30))
 ------------------------------PhysicalOlapScan[time_dim]
 ----------------------PhysicalProject
-------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+------------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 --------------------------PhysicalOlapScan[household_demographics]
 ------------------PhysicalProject
 --------------------filter((store.s_store_name = 'ese'))
@@ -143,7 +143,7 @@ PhysicalResultSink
 --------------------------filter((time_dim.t_hour = 11) and (time_dim.t_minute >= 30))
 ----------------------------PhysicalOlapScan[time_dim]
 --------------------PhysicalProject
-----------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+----------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ------------------------PhysicalOlapScan[household_demographics]
 ----------------PhysicalProject
 ------------------filter((store.s_store_name = 'ese'))
@@ -163,7 +163,7 @@ PhysicalResultSink
 ------------------------filter((time_dim.t_hour = 12) and (time_dim.t_minute < 30))
 --------------------------PhysicalOlapScan[time_dim]
 ------------------PhysicalProject
---------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))) and hd_dep_count IN (-1, 0, 3) and hd_dep_count IN (-1, 0, 3))
+--------------------filter(((((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= 2)) OR ((household_demographics.hd_dep_count = -1) AND (household_demographics.hd_vehicle_count <= 1))) OR ((household_demographics.hd_dep_count = 3) AND (household_demographics.hd_vehicle_count <= 5))))
 ----------------------PhysicalOlapScan[household_demographics]
 --------------PhysicalProject
 ----------------filter((store.s_store_name = 'ese'))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query89.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query89.out
index 786de940dad5d8..64708542abb732 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query89.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query89.out
@@ -23,7 +23,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2
 ----------------------------------------PhysicalProject
-------------------------------------------filter(((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('audio', 'history', 'school-uniforms')) OR (i_category IN ('Men', 'Shoes', 'Sports') AND i_class IN ('pants', 'tennis', 'womens'))) and i_category IN ('Books', 'Children', 'Electronics', 'Men', 'Shoes', 'Sports') and i_class IN ('audio', 'history', 'pants', 'school-uniforms', 'tennis', 'womens'))
+------------------------------------------filter(((i_category IN ('Books', 'Children', 'Electronics') AND i_class IN ('audio', 'history', 'school-uniforms')) OR (i_category IN ('Men', 'Shoes', 'Sports') AND i_class IN ('pants', 'tennis', 'womens'))))
 --------------------------------------------PhysicalOlapScan[item]
 ------------------------------------PhysicalProject
 --------------------------------------filter((date_dim.d_year = 2001))
diff --git a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query91.out b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query91.out
index 624685e9dab961..69fe2228399236 100644
--- a/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query91.out
+++ b/regression-test/data/new_shapes_p0/tpcds_sf1000/shape/query91.out
@@ -28,7 +28,7 @@ PhysicalResultSink
 ----------------------------------------PhysicalProject
 ------------------------------------------PhysicalOlapScan[customer] apply RFs: RF0 RF1
 ----------------------------------------PhysicalProject
-------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))) and cd_education_status IN ('Advanced Degree', 'Unknown') and cd_marital_status IN ('M', 'W'))
+------------------------------------------filter((((customer_demographics.cd_marital_status = 'M') AND (customer_demographics.cd_education_status = 'Unknown')) OR ((customer_demographics.cd_marital_status = 'W') AND (customer_demographics.cd_education_status = 'Advanced Degree'))))
 --------------------------------------------PhysicalOlapScan[customer_demographics]
 ------------------------------------PhysicalProject
 --------------------------------------filter((hd_buy_potential like 'Unknown%'))
diff --git a/regression-test/data/new_shapes_p0/tpch_sf1000/nostats_rf_prune/q19.out b/regression-test/data/new_shapes_p0/tpch_sf1000/nostats_rf_prune/q19.out
index bf86e68a7f9837..8f425073388280 100644
--- a/regression-test/data/new_shapes_p0/tpch_sf1000/nostats_rf_prune/q19.out
+++ b/regression-test/data/new_shapes_p0/tpch_sf1000/nostats_rf_prune/q19.out
@@ -5,11 +5,11 @@ PhysicalResultSink
 ----PhysicalDistribute[DistributionSpecGather]
 ------hashAgg[LOCAL]
 --------PhysicalProject
-----------hashJoin[INNER_JOIN broadcast] hashCondition=((part.p_partkey = lineitem.l_partkey)) otherCondition=(((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND ((lineitem.l_quantity >= 1.00) AND (lineitem.l_quantity <= 11.00))) AND (part.p_size <= 5)) OR ((((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND ((lineitem.l_quantity >= 10.00) AND (lineitem.l_quantity <= 20.00))) AND (part.p_size <= 10))) OR ((((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND ((lineitem.l_quantity >= 20.00) AND (lineitem.l_quantity <= 30.00))) AND (part.p_size <= 15)))) build RFs:RF0 p_partkey->[l_partkey]
+----------hashJoin[INNER_JOIN shuffleBucket] hashCondition=((part.p_partkey = lineitem.l_partkey)) otherCondition=(((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND ((lineitem.l_quantity >= 1.00) AND (lineitem.l_quantity <= 11.00))) AND (part.p_size <= 5)) OR ((((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND ((lineitem.l_quantity >= 10.00) AND (lineitem.l_quantity <= 20.00))) AND (part.p_size <= 10))) OR ((((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND ((lineitem.l_quantity >= 20.00) AND (lineitem.l_quantity <= 30.00))) AND (part.p_size <= 15)))) build RFs:RF0 p_partkey->[l_partkey]
 ------------PhysicalProject
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem] apply RFs: RF0
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
diff --git a/regression-test/data/new_shapes_p0/tpch_sf1000/rf_prune/q19.out b/regression-test/data/new_shapes_p0/tpch_sf1000/rf_prune/q19.out
index bf86e68a7f9837..60e7b8446bd1a0 100644
--- a/regression-test/data/new_shapes_p0/tpch_sf1000/rf_prune/q19.out
+++ b/regression-test/data/new_shapes_p0/tpch_sf1000/rf_prune/q19.out
@@ -10,6 +10,6 @@ PhysicalResultSink
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem] apply RFs: RF0
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
diff --git a/regression-test/data/new_shapes_p0/tpch_sf1000/shape/q19.out b/regression-test/data/new_shapes_p0/tpch_sf1000/shape/q19.out
index bf86e68a7f9837..60e7b8446bd1a0 100644
--- a/regression-test/data/new_shapes_p0/tpch_sf1000/shape/q19.out
+++ b/regression-test/data/new_shapes_p0/tpch_sf1000/shape/q19.out
@@ -10,6 +10,6 @@ PhysicalResultSink
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem] apply RFs: RF0
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
diff --git a/regression-test/data/new_shapes_p0/tpch_sf1000/shape_no_stats/q19.out b/regression-test/data/new_shapes_p0/tpch_sf1000/shape_no_stats/q19.out
index bf86e68a7f9837..8f425073388280 100644
--- a/regression-test/data/new_shapes_p0/tpch_sf1000/shape_no_stats/q19.out
+++ b/regression-test/data/new_shapes_p0/tpch_sf1000/shape_no_stats/q19.out
@@ -5,11 +5,11 @@ PhysicalResultSink
 ----PhysicalDistribute[DistributionSpecGather]
 ------hashAgg[LOCAL]
 --------PhysicalProject
-----------hashJoin[INNER_JOIN broadcast] hashCondition=((part.p_partkey = lineitem.l_partkey)) otherCondition=(((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND ((lineitem.l_quantity >= 1.00) AND (lineitem.l_quantity <= 11.00))) AND (part.p_size <= 5)) OR ((((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND ((lineitem.l_quantity >= 10.00) AND (lineitem.l_quantity <= 20.00))) AND (part.p_size <= 10))) OR ((((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND ((lineitem.l_quantity >= 20.00) AND (lineitem.l_quantity <= 30.00))) AND (part.p_size <= 15)))) build RFs:RF0 p_partkey->[l_partkey]
+----------hashJoin[INNER_JOIN shuffleBucket] hashCondition=((part.p_partkey = lineitem.l_partkey)) otherCondition=(((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND ((lineitem.l_quantity >= 1.00) AND (lineitem.l_quantity <= 11.00))) AND (part.p_size <= 5)) OR ((((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND ((lineitem.l_quantity >= 10.00) AND (lineitem.l_quantity <= 20.00))) AND (part.p_size <= 10))) OR ((((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND ((lineitem.l_quantity >= 20.00) AND (lineitem.l_quantity <= 30.00))) AND (part.p_size <= 15)))) build RFs:RF0 p_partkey->[l_partkey]
 ------------PhysicalProject
 --------------filter((lineitem.l_quantity <= 30.00) and (lineitem.l_quantity >= 1.00) and (lineitem.l_shipinstruct = 'DELIVER IN PERSON') and l_shipmode IN ('AIR REG', 'AIR'))
 ----------------PhysicalOlapScan[lineitem] apply RFs: RF0
 ------------PhysicalProject
---------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1) and p_brand IN ('Brand#12', 'Brand#23', 'Brand#34') and p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG', 'MED BAG', 'MED BOX', 'MED PACK', 'MED PKG', 'SM BOX', 'SM CASE', 'SM PACK', 'SM PKG'))
+--------------filter((((((part.p_brand = 'Brand#12') AND p_container IN ('SM BOX', 'SM CASE', 'SM PACK', 'SM PKG')) AND (part.p_size <= 5)) OR (((part.p_brand = 'Brand#23') AND p_container IN ('MED BAG', 'MED BOX', 'MED PACK', 'MED PKG')) AND (part.p_size <= 10))) OR (((part.p_brand = 'Brand#34') AND p_container IN ('LG BOX', 'LG CASE', 'LG PACK', 'LG PKG')) AND (part.p_size <= 15))) and (part.p_size >= 1))
 ----------------PhysicalOlapScan[part]
 
diff --git a/regression-test/suites/nereids_hint_tpch_p0/shape/q4.groovy b/regression-test/suites/nereids_hint_tpch_p0/shape/q4.groovy
index 7ad2751c86c2a1..cc3c19f91094fd 100644
--- a/regression-test/suites/nereids_hint_tpch_p0/shape/q4.groovy
+++ b/regression-test/suites/nereids_hint_tpch_p0/shape/q4.groovy
@@ -39,29 +39,29 @@ suite("q4") {
 sql 'set be_number_for_test=3'
 
 
-    // qt_select """
-    // explain shape plan
-    // select  
-    // /*+ leading(lineitem orders) */
-    //     o_orderpriority,
-    //     count(*) as order_count
-    // from
-    //     orders
-    // where
-    //     o_orderdate >= date '1993-07-01'
-    //     and o_orderdate < date '1993-07-01' + interval '3' month
-    //     and exists (
-    //         select
-    //             *
-    //         from
-    //             lineitem
-    //         where
-    //             l_orderkey = o_orderkey
-    //             and l_commitdate < l_receiptdate
-    //     )
-    // group by
-    //     o_orderpriority
-    // order by
-    //     o_orderpriority;
-    // """
+    qt_select """
+    explain shape plan
+    select  
+    /*+ leading(lineitem orders) */
+        o_orderpriority,
+        count(*) as order_count
+    from
+        orders
+    where
+        o_orderdate >= date '1993-07-01'
+        and o_orderdate < date '1993-07-01' + interval '3' month
+        and exists (
+            select
+                *
+            from
+                lineitem
+            where
+                l_orderkey = o_orderkey
+                and l_commitdate < l_receiptdate
+        )
+    group by
+        o_orderpriority
+    order by
+        o_orderpriority;
+    """
 }