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* Added rescorer in hybrid query (#917) * Initial version for rescorer Signed-off-by: Martin Gaievski <[email protected]> (cherry picked from commit 9f4a49a) Signed-off-by: Martin Gaievski <[email protected]>
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150 changes: 150 additions & 0 deletions
150
...ling-upgrade/src/test/java/org/opensearch/neuralsearch/bwc/HybridSearchWithRescoreIT.java
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/* | ||
* Copyright OpenSearch Contributors | ||
* SPDX-License-Identifier: Apache-2.0 | ||
*/ | ||
package org.opensearch.neuralsearch.bwc; | ||
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import org.opensearch.index.query.MatchQueryBuilder; | ||
import org.opensearch.index.query.QueryBuilder; | ||
import org.opensearch.index.query.QueryBuilders; | ||
import org.opensearch.knn.index.query.rescore.RescoreContext; | ||
import org.opensearch.neuralsearch.query.HybridQueryBuilder; | ||
import org.opensearch.neuralsearch.query.NeuralQueryBuilder; | ||
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import java.nio.file.Files; | ||
import java.nio.file.Path; | ||
import java.util.Arrays; | ||
import java.util.List; | ||
import java.util.Map; | ||
import java.util.Objects; | ||
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import static org.opensearch.neuralsearch.util.TestUtils.NODES_BWC_CLUSTER; | ||
import static org.opensearch.neuralsearch.util.TestUtils.PARAM_NAME_WEIGHTS; | ||
import static org.opensearch.neuralsearch.util.TestUtils.TEXT_EMBEDDING_PROCESSOR; | ||
import static org.opensearch.neuralsearch.util.TestUtils.DEFAULT_NORMALIZATION_METHOD; | ||
import static org.opensearch.neuralsearch.util.TestUtils.DEFAULT_COMBINATION_METHOD; | ||
import static org.opensearch.neuralsearch.util.TestUtils.getModelId; | ||
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public class HybridSearchWithRescoreIT extends AbstractRollingUpgradeTestCase { | ||
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private static final String PIPELINE_NAME = "nlp-hybrid-with-rescore-pipeline"; | ||
private static final String SEARCH_PIPELINE_NAME = "nlp-search-with_rescore-pipeline"; | ||
private static final String TEST_FIELD = "passage_text"; | ||
private static final String TEXT = "Hello world"; | ||
private static final String TEXT_MIXED = "Hi planet"; | ||
private static final String TEXT_UPGRADED = "Hi earth"; | ||
private static final String QUERY = "Hi world"; | ||
private static final int NUM_DOCS_PER_ROUND = 1; | ||
private static final String VECTOR_EMBEDDING_FIELD = "passage_embedding"; | ||
protected static final String RESCORE_QUERY = "hi"; | ||
private static String modelId = ""; | ||
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/** | ||
* Test normalization with hybrid query and rescore. This test is required as rescore will not be compatible with version lower than 2.15 | ||
*/ | ||
public void testHybridQueryWithRescore_whenIndexWithMultipleShards_E2EFlow() throws Exception { | ||
waitForClusterHealthGreen(NODES_BWC_CLUSTER); | ||
switch (getClusterType()) { | ||
case OLD: | ||
modelId = uploadTextEmbeddingModel(); | ||
loadModel(modelId); | ||
createPipelineProcessor(modelId, PIPELINE_NAME); | ||
createIndexWithConfiguration( | ||
getIndexNameForTest(), | ||
Files.readString(Path.of(classLoader.getResource("processor/IndexMappings.json").toURI())), | ||
PIPELINE_NAME | ||
); | ||
addDocument(getIndexNameForTest(), "0", TEST_FIELD, TEXT, null, null); | ||
createSearchPipeline( | ||
SEARCH_PIPELINE_NAME, | ||
DEFAULT_NORMALIZATION_METHOD, | ||
DEFAULT_COMBINATION_METHOD, | ||
Map.of(PARAM_NAME_WEIGHTS, Arrays.toString(new float[] { 0.3f, 0.7f })) | ||
); | ||
break; | ||
case MIXED: | ||
modelId = getModelId(getIngestionPipeline(PIPELINE_NAME), TEXT_EMBEDDING_PROCESSOR); | ||
int totalDocsCountMixed; | ||
if (isFirstMixedRound()) { | ||
totalDocsCountMixed = NUM_DOCS_PER_ROUND; | ||
HybridQueryBuilder hybridQueryBuilder = getQueryBuilder(modelId, null, null); | ||
QueryBuilder rescorer = QueryBuilders.matchQuery(TEST_FIELD, RESCORE_QUERY).boost(0.3f); | ||
validateTestIndexOnUpgrade(totalDocsCountMixed, modelId, hybridQueryBuilder, rescorer); | ||
addDocument(getIndexNameForTest(), "1", TEST_FIELD, TEXT_MIXED, null, null); | ||
} else { | ||
totalDocsCountMixed = 2 * NUM_DOCS_PER_ROUND; | ||
HybridQueryBuilder hybridQueryBuilder = getQueryBuilder(modelId, null, null); | ||
validateTestIndexOnUpgrade(totalDocsCountMixed, modelId, hybridQueryBuilder, null); | ||
} | ||
break; | ||
case UPGRADED: | ||
try { | ||
modelId = getModelId(getIngestionPipeline(PIPELINE_NAME), TEXT_EMBEDDING_PROCESSOR); | ||
int totalDocsCountUpgraded = 3 * NUM_DOCS_PER_ROUND; | ||
loadModel(modelId); | ||
addDocument(getIndexNameForTest(), "2", TEST_FIELD, TEXT_UPGRADED, null, null); | ||
HybridQueryBuilder hybridQueryBuilder = getQueryBuilder(modelId, null, null); | ||
QueryBuilder rescorer = QueryBuilders.matchQuery(TEST_FIELD, RESCORE_QUERY).boost(0.3f); | ||
validateTestIndexOnUpgrade(totalDocsCountUpgraded, modelId, hybridQueryBuilder, rescorer); | ||
hybridQueryBuilder = getQueryBuilder(modelId, Map.of("ef_search", 100), RescoreContext.getDefault()); | ||
validateTestIndexOnUpgrade(totalDocsCountUpgraded, modelId, hybridQueryBuilder, rescorer); | ||
} finally { | ||
wipeOfTestResources(getIndexNameForTest(), PIPELINE_NAME, modelId, SEARCH_PIPELINE_NAME); | ||
} | ||
break; | ||
default: | ||
throw new IllegalStateException("Unexpected value: " + getClusterType()); | ||
} | ||
} | ||
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private void validateTestIndexOnUpgrade( | ||
final int numberOfDocs, | ||
final String modelId, | ||
HybridQueryBuilder hybridQueryBuilder, | ||
QueryBuilder rescorer | ||
) throws Exception { | ||
int docCount = getDocCount(getIndexNameForTest()); | ||
assertEquals(numberOfDocs, docCount); | ||
loadModel(modelId); | ||
Map<String, Object> searchResponseAsMap = search( | ||
getIndexNameForTest(), | ||
hybridQueryBuilder, | ||
rescorer, | ||
1, | ||
Map.of("search_pipeline", SEARCH_PIPELINE_NAME) | ||
); | ||
assertNotNull(searchResponseAsMap); | ||
int hits = getHitCount(searchResponseAsMap); | ||
assertEquals(1, hits); | ||
List<Double> scoresList = getNormalizationScoreList(searchResponseAsMap); | ||
for (Double score : scoresList) { | ||
assertTrue(0 <= score && score <= 2); | ||
} | ||
} | ||
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private HybridQueryBuilder getQueryBuilder( | ||
final String modelId, | ||
final Map<String, ?> methodParameters, | ||
final RescoreContext rescoreContextForNeuralQuery | ||
) { | ||
NeuralQueryBuilder neuralQueryBuilder = new NeuralQueryBuilder(); | ||
neuralQueryBuilder.fieldName(VECTOR_EMBEDDING_FIELD); | ||
neuralQueryBuilder.modelId(modelId); | ||
neuralQueryBuilder.queryText(QUERY); | ||
neuralQueryBuilder.k(5); | ||
if (methodParameters != null) { | ||
neuralQueryBuilder.methodParameters(methodParameters); | ||
} | ||
if (Objects.nonNull(rescoreContextForNeuralQuery)) { | ||
neuralQueryBuilder.rescoreContext(rescoreContextForNeuralQuery); | ||
} | ||
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MatchQueryBuilder matchQueryBuilder = new MatchQueryBuilder("text", QUERY); | ||
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HybridQueryBuilder hybridQueryBuilder = new HybridQueryBuilder(); | ||
hybridQueryBuilder.add(matchQueryBuilder); | ||
hybridQueryBuilder.add(neuralQueryBuilder); | ||
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return hybridQueryBuilder; | ||
} | ||
} |
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17 changes: 17 additions & 0 deletions
17
...org/opensearch/neuralsearch/search/query/exception/HybridSearchRescoreQueryException.java
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/* | ||
* Copyright OpenSearch Contributors | ||
* SPDX-License-Identifier: Apache-2.0 | ||
*/ | ||
package org.opensearch.neuralsearch.search.query.exception; | ||
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import org.opensearch.OpenSearchException; | ||
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/** | ||
* Exception thrown when there is an issue with the hybrid search rescore query. | ||
*/ | ||
public class HybridSearchRescoreQueryException extends OpenSearchException { | ||
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public HybridSearchRescoreQueryException(Throwable cause) { | ||
super("rescore failed for hybrid query", cause); | ||
} | ||
} |
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344 changes: 344 additions & 0 deletions
344
src/test/java/org/opensearch/neuralsearch/search/query/HybridCollectorManagerTests.java
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