update shape plan

regression-test/data/nereids_ssb_shape_sf100_p0/shape/flat.out

@@ -0,0 +1,17 @@
+-- This file is automatically generated. You should know what you did if you want to edit this
+-- !select --
+PhysicalResultSink
+--PhysicalDistribute
+----PhysicalProject
+------hashJoin[INNER_JOIN] hashCondition=((s.s_suppkey = l.lo_suppkey)) otherCondition=() build RFs:RF2 s_suppkey->[lo_suppkey]
+--------PhysicalProject
+----------hashJoin[INNER_JOIN] hashCondition=((c.c_custkey = l.lo_custkey)) otherCondition=() build RFs:RF1 c_custkey->[lo_custkey]
+------------hashJoin[INNER_JOIN] hashCondition=((p.p_partkey = l.lo_partkey)) otherCondition=() build RFs:RF0 p_partkey->[lo_partkey]
+--------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
+--------------PhysicalDistribute
+----------------PhysicalOlapScan[part]
+------------PhysicalDistribute
+--------------PhysicalOlapScan[customer]
+--------PhysicalDistribute
+----------PhysicalOlapScan[supplier]
+

regression-test/data/nereids_ssb_shape_sf100_p0/shape/q2.2.out

@@ -9,21 +9,19 @@ PhysicalResultSink
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
 ----------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_orderdate = dates.d_datekey)) otherCondition=() build RFs:RF2 d_datekey->[lo_orderdate]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_suppkey = supplier.s_suppkey)) otherCondition=() build RFs:RF1 s_suppkey->[lo_suppkey]
-------------------------PhysicalDistribute
---------------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_partkey = part.p_partkey)) otherCondition=() build RFs:RF0 p_partkey->[lo_partkey]
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter((part.p_brand <= 'MFGR#2228') and (part.p_brand >= 'MFGR#2221'))
-----------------------------------PhysicalOlapScan[part]
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_suppkey = supplier.s_suppkey)) otherCondition=() build RFs:RF1 s_suppkey->[lo_suppkey]
+----------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_partkey = part.p_partkey)) otherCondition=() build RFs:RF0 p_partkey->[lo_partkey]
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter((supplier.s_region = 'ASIA'))
-------------------------------PhysicalOlapScan[supplier]
+----------------------------filter((part.p_brand <= 'MFGR#2228') and (part.p_brand >= 'MFGR#2221'))
+------------------------------PhysicalOlapScan[part]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((supplier.s_region = 'ASIA'))
+----------------------------PhysicalOlapScan[supplier]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
 ----------------------PhysicalOlapScan[dates]

regression-test/data/nereids_ssb_shape_sf100_p0/shape/q2.3.out

@@ -9,21 +9,19 @@ PhysicalResultSink
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
 ----------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_orderdate = dates.d_datekey)) otherCondition=() build RFs:RF2 d_datekey->[lo_orderdate]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_suppkey = supplier.s_suppkey)) otherCondition=() build RFs:RF1 s_suppkey->[lo_suppkey]
-------------------------PhysicalDistribute
---------------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_partkey = part.p_partkey)) otherCondition=() build RFs:RF0 p_partkey->[lo_partkey]
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter((part.p_brand = 'MFGR#2239'))
-----------------------------------PhysicalOlapScan[part]
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_suppkey = supplier.s_suppkey)) otherCondition=() build RFs:RF1 s_suppkey->[lo_suppkey]
+----------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_partkey = part.p_partkey)) otherCondition=() build RFs:RF0 p_partkey->[lo_partkey]
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter((supplier.s_region = 'EUROPE'))
-------------------------------PhysicalOlapScan[supplier]
+----------------------------filter((part.p_brand = 'MFGR#2239'))
+------------------------------PhysicalOlapScan[part]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter((supplier.s_region = 'EUROPE'))
+----------------------------PhysicalOlapScan[supplier]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
 ----------------------PhysicalOlapScan[dates]

regression-test/data/nereids_ssb_shape_sf100_p0/shape/q3.3.out

@@ -9,21 +9,19 @@ PhysicalResultSink
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
 ----------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_orderdate = dates.d_datekey)) otherCondition=() build RFs:RF2 d_datekey->[lo_orderdate]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_custkey = customer.c_custkey)) otherCondition=() build RFs:RF1 c_custkey->[lo_custkey]
-------------------------PhysicalDistribute
---------------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_suppkey = supplier.s_suppkey)) otherCondition=() build RFs:RF0 s_suppkey->[lo_suppkey]
-----------------------------PhysicalProject
-------------------------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter(s_city IN ('UNITED KI1', 'UNITED KI5'))
-----------------------------------PhysicalOlapScan[supplier]
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_custkey = customer.c_custkey)) otherCondition=() build RFs:RF1 c_custkey->[lo_custkey]
+----------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_suppkey = supplier.s_suppkey)) otherCondition=() build RFs:RF0 s_suppkey->[lo_suppkey]
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter(c_city IN ('UNITED KI1', 'UNITED KI5'))
-------------------------------PhysicalOlapScan[customer]
+----------------------------filter(s_city IN ('UNITED KI1', 'UNITED KI5'))
+------------------------------PhysicalOlapScan[supplier]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter(c_city IN ('UNITED KI1', 'UNITED KI5'))
+----------------------------PhysicalOlapScan[customer]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
 ----------------------filter((dates.d_year <= 1997) and (dates.d_year >= 1992))

regression-test/data/nereids_ssb_shape_sf100_p0/shape/q3.4.out

@@ -8,23 +8,22 @@ PhysicalResultSink
 ----------PhysicalDistribute
 ------------hashAgg[LOCAL]
 --------------PhysicalProject
-----------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_custkey = customer.c_custkey)) otherCondition=() build RFs:RF2 c_custkey->[lo_custkey]
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_orderdate = dates.d_datekey)) otherCondition=() build RFs:RF1 d_datekey->[lo_orderdate]
-------------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_suppkey = supplier.s_suppkey)) otherCondition=() build RFs:RF0 s_suppkey->[lo_suppkey]
---------------------------PhysicalProject
-----------------------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
---------------------------PhysicalDistribute
-----------------------------PhysicalProject
-------------------------------filter(s_city IN ('UNITED KI1', 'UNITED KI5'))
---------------------------------PhysicalOlapScan[supplier]
+----------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_orderdate = dates.d_datekey)) otherCondition=() build RFs:RF2 d_datekey->[lo_orderdate]
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_custkey = customer.c_custkey)) otherCondition=() build RFs:RF1 c_custkey->[lo_custkey]
+----------------------hashJoin[INNER_JOIN] hashCondition=((lineorder.lo_suppkey = supplier.s_suppkey)) otherCondition=() build RFs:RF0 s_suppkey->[lo_suppkey]
+------------------------PhysicalProject
+--------------------------PhysicalOlapScan[lineorder] apply RFs: RF0 RF1 RF2
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter((dates.d_yearmonth = 'Dec1997'))
-------------------------------PhysicalOlapScan[dates]
+----------------------------filter(s_city IN ('UNITED KI1', 'UNITED KI5'))
+------------------------------PhysicalOlapScan[supplier]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter(c_city IN ('UNITED KI1', 'UNITED KI5'))
+----------------------------PhysicalOlapScan[customer]
 ------------------PhysicalDistribute
 --------------------PhysicalProject
-----------------------filter(c_city IN ('UNITED KI1', 'UNITED KI5'))
-------------------------PhysicalOlapScan[customer]
+----------------------filter((dates.d_yearmonth = 'Dec1997'))
+------------------------PhysicalOlapScan[dates]
 

regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query10.out

@@ -26,8 +26,7 @@ PhysicalResultSink
 ----------------------------hashJoin[LEFT_SEMI_JOIN] hashCondition=((c.c_customer_sk = web_sales.ws_bill_customer_sk)) otherCondition=()
 ------------------------------PhysicalProject
 --------------------------------hashJoin[INNER_JOIN] hashCondition=((customer_demographics.cd_demo_sk = c.c_current_cdemo_sk)) otherCondition=() build RFs:RF3 c_current_cdemo_sk->[cd_demo_sk]
-----------------------------------PhysicalDistribute
-------------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
+----------------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
 ----------------------------------PhysicalDistribute
 ------------------------------------PhysicalProject
 --------------------------------------hashJoin[INNER_JOIN] hashCondition=((c.c_current_addr_sk = ca.ca_address_sk)) otherCondition=() build RFs:RF2 ca_address_sk->[c_current_addr_sk]

regression-test/data/nereids_tpcds_shape_sf1000_p0/shape/query13.out

@@ -6,34 +6,33 @@ PhysicalResultSink
 ------hashAgg[LOCAL]
 --------PhysicalProject
 ----------hashJoin[INNER_JOIN] hashCondition=((store.s_store_sk = store_sales.ss_store_sk)) otherCondition=() build RFs:RF4 s_store_sk->[ss_store_sk]
-------------PhysicalDistribute
---------------PhysicalProject
-----------------hashJoin[INNER_JOIN] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=(((((((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)) OR ((((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))) AND (household_demographics.hd_dep_count = 1))) 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))) AND (household_demographics.hd_dep_count = 1)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
-------------------PhysicalDistribute
---------------------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'))))
-------------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
-------------------PhysicalDistribute
---------------------PhysicalProject
-----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=() build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
-------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[ss_sold_date_sk]
---------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IL', 'TN', 'TX') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('ID', 'OH', 'WY') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00)))) OR (ca_state IN ('IA', 'MS', 'SC') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))))) build RFs:RF0 ca_address_sk->[ss_addr_sk]
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter(((((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00)) OR ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00))) OR ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))) and ((((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00)) OR ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))
-----------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF4
-----------------------------PhysicalDistribute
-------------------------------PhysicalProject
---------------------------------filter(((ca_state IN ('IL', 'TN', 'TX') OR ca_state IN ('ID', 'OH', 'WY')) OR ca_state IN ('IA', 'MS', 'SC')) and (customer_address.ca_country = 'United States'))
-----------------------------------PhysicalOlapScan[customer_address]
+------------PhysicalProject
+--------------hashJoin[INNER_JOIN] hashCondition=((customer_demographics.cd_demo_sk = store_sales.ss_cdemo_sk)) otherCondition=(((((((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)) OR ((((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))) AND (household_demographics.hd_dep_count = 1))) 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))) AND (household_demographics.hd_dep_count = 1)))) build RFs:RF3 ss_cdemo_sk->[cd_demo_sk]
+----------------PhysicalDistribute
+------------------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'))))
+----------------------PhysicalOlapScan[customer_demographics] apply RFs: RF3
+----------------PhysicalDistribute
+------------------PhysicalProject
+--------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk)) otherCondition=() build RFs:RF2 hd_demo_sk->[ss_hdemo_sk]
+----------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_sold_date_sk = date_dim.d_date_sk)) otherCondition=() build RFs:RF1 d_date_sk->[ss_sold_date_sk]
+------------------------hashJoin[INNER_JOIN] hashCondition=((store_sales.ss_addr_sk = customer_address.ca_address_sk)) otherCondition=((((ca_state IN ('IL', 'TN', 'TX') AND ((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00))) OR (ca_state IN ('ID', 'OH', 'WY') AND ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00)))) OR (ca_state IN ('IA', 'MS', 'SC') AND ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))))) build RFs:RF0 ca_address_sk->[ss_addr_sk]
+--------------------------PhysicalDistribute
+----------------------------PhysicalProject
+------------------------------filter(((((store_sales.ss_net_profit >= 100.00) AND (store_sales.ss_net_profit <= 200.00)) OR ((store_sales.ss_net_profit >= 150.00) AND (store_sales.ss_net_profit <= 300.00))) OR ((store_sales.ss_net_profit >= 50.00) AND (store_sales.ss_net_profit <= 250.00))) and ((((store_sales.ss_sales_price >= 100.00) AND (store_sales.ss_sales_price <= 150.00)) OR ((store_sales.ss_sales_price >= 50.00) AND (store_sales.ss_sales_price <= 100.00))) OR ((store_sales.ss_sales_price >= 150.00) AND (store_sales.ss_sales_price <= 200.00))))
+--------------------------------PhysicalOlapScan[store_sales] apply RFs: RF0 RF1 RF2 RF4
 --------------------------PhysicalDistribute
 ----------------------------PhysicalProject
-------------------------------filter((date_dim.d_year = 2001))
---------------------------------PhysicalOlapScan[date_dim]
+------------------------------filter(((ca_state IN ('IL', 'TN', 'TX') OR ca_state IN ('ID', 'OH', 'WY')) OR ca_state IN ('IA', 'MS', 'SC')) and (customer_address.ca_country = 'United States'))
+--------------------------------PhysicalOlapScan[customer_address]
 ------------------------PhysicalDistribute
 --------------------------PhysicalProject
-----------------------------filter(((household_demographics.hd_dep_count = 3) OR (household_demographics.hd_dep_count = 1)))
-------------------------------PhysicalOlapScan[household_demographics]
+----------------------------filter((date_dim.d_year = 2001))
+------------------------------PhysicalOlapScan[date_dim]
+----------------------PhysicalDistribute
+------------------------PhysicalProject
+--------------------------filter(((household_demographics.hd_dep_count = 3) OR (household_demographics.hd_dep_count = 1)))
+----------------------------PhysicalOlapScan[household_demographics]
 ------------PhysicalDistribute
 --------------PhysicalProject
 ----------------PhysicalOlapScan[store]