Merge branch 'main' into support-embedding-types

Signed-off-by: Martin Gaievski <gaievski@amazon.com>

Author: martin-gaievski

.github/workflows/CI.yml

@@ -117,28 +117,6 @@ jobs:
           name: coverage-report-${{ matrix.os }}-${{ matrix.java }}
           path: ./jacocoTestReport.xml
 
-  Precommit-neural-search-windows:
-    strategy:
-      matrix:
-        java: [21, 23]
-        os: [windows-latest]
-
-    name: Pre-commit Windows
-    runs-on: ${{ matrix.os }}
-
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Setup Java ${{ matrix.java }}
-        uses: actions/setup-java@v4
-        with:
-          distribution: 'temurin'
-          java-version: ${{ matrix.java }}
-
-      - name: Run build
-        run: |
-          ./gradlew precommit --parallel
-
   Precommit-codecov:
     needs: Precommit-neural-search-linux
     strategy:

.github/workflows/backwards_compatibility_tests_workflow.yml

@@ -13,9 +13,9 @@ jobs:
   Restart-Upgrade-BWCTests-NeuralSearch:
     strategy:
       matrix:
-        java: [21, 23]
-        os: [ubuntu-latest,windows-latest]
-        bwc_version : ["2.9.0","2.10.0","2.11.0","2.12.0","2.13.0","2.14.0","2.15.0","2.16.0","2.17.0","2.18.0","2.19.0-SNAPSHOT"]
+        java: [ 21, 23 ]
+        os: [ubuntu-latest]
+        bwc_version : ["2.9.0","2.10.0","2.11.0","2.12.0","2.13.0","2.14.0","2.15.0","2.16.0","2.17.0","2.18.0","2.19.0","2.20.0-SNAPSHOT"]
         opensearch_version : [ "3.0.0-SNAPSHOT" ]
 
     name: NeuralSearch Restart-Upgrade BWC Tests
@@ -42,7 +42,7 @@ jobs:
       matrix:
         java: [21, 23]
         os: [ubuntu-latest,windows-latest]
-        bwc_version: [ "2.19.0-SNAPSHOT" ]
+        bwc_version: [ "2.20.0-SNAPSHOT" ]
         opensearch_version: [ "3.0.0-SNAPSHOT" ]
 
     name: NeuralSearch Rolling-Upgrade BWC Tests

.github/workflows/test_aggregations.yml

@@ -54,7 +54,7 @@ jobs:
   Check-neural-search-windows:
     strategy:
       matrix:
-        java: [21, 23]
+        java: [23]
         os: [windows-latest]
 
     name: Integ Tests Windows

CHANGELOG.md

@@ -6,10 +6,11 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 ## [Unreleased 3.0](https://github.com/opensearch-project/neural-search/compare/2.x...HEAD)
 ### Features
 ### Enhancements
-- Set neural-search plugin 3.0.0 baseline JDK version to JDK-2 ([#838](https://github.com/opensearch-project/neural-search/pull/838))
+- Set neural-search plugin 3.0.0 baseline JDK version to JDK-21 ([#838](https://github.com/opensearch-project/neural-search/pull/838))
 - Support different embedding types in model's response ([#1007](https://github.com/opensearch-project/neural-search/pull/1007))
 ### Bug Fixes
 ### Infrastructure
+- [3.0] Update neural-search for OpenSearch 3.0 compatibility ([#1141](https://github.com/opensearch-project/neural-search/pull/1141))
 ### Documentation
 ### Maintenance
 ### Refactoring

build.gradle

@@ -14,8 +14,8 @@ import java.util.concurrent.Callable
 
 buildscript {
     ext {
-        opensearch_version = System.getProperty("opensearch.version", "3.0.0-SNAPSHOT")
-        buildVersionQualifier = System.getProperty("build.version_qualifier", "")
+        opensearch_version = System.getProperty("opensearch.version", "3.0.0-alpha1-SNAPSHOT")
+        buildVersionQualifier = System.getProperty("build.version_qualifier", "alpha1")
         isSnapshot = "true" == System.getProperty("build.snapshot", "true")
         version_tokens = opensearch_version.tokenize('-')
         opensearch_build = version_tokens[0] + '.0'

gradle.properties

@@ -7,7 +7,7 @@
 # https://github.com/opensearch-project/OpenSearch/blob/main/libs/core/src/main/java/org/opensearch/Version.java .
 # Wired compatibility of OpenSearch works like 3.x version is compatible with 2.(latest-major) version.
 # Therefore, to run rolling-upgrade BWC Test on local machine the BWC version here should be set 2.(latest-major).
-systemProp.bwc.version=2.19.0-SNAPSHOT
+systemProp.bwc.version=2.20.0-SNAPSHOT
 systemProp.bwc.bundle.version=2.19.0
 
 # For fixing Spotless check with Java 17

gradle/wrapper/gradle-wrapper.properties

@@ -1,3 +1,8 @@
+#
+#  Copyright OpenSearch Contributors
+#  SPDX-License-Identifier: Apache-2.0
+#
+
 distributionBase=GRADLE_USER_HOME
 distributionPath=wrapper/dists
 distributionSha256Sum=2ab88d6de2c23e6adae7363ae6e29cbdd2a709e992929b48b6530fd0c7133bd6

gradlew

@@ -1,4 +1,8 @@
 #!/bin/sh
+#
+#  Copyright OpenSearch Contributors
+#  SPDX-License-Identifier: Apache-2.0
+#
 
 #
 # Copyright © 2015-2021 the original authors.

gradlew.bat

@@ -1,4 +1,7 @@
 @rem
+@rem  Copyright OpenSearch Contributors
+@rem  SPDX-License-Identifier: Apache-2.0
+@rem
 @rem Copyright 2015 the original author or authors.
 @rem
 @rem Licensed under the Apache License, Version 2.0 (the "License");

qa/rolling-upgrade/src/test/java/org/opensearch/neuralsearch/bwc/rolling/AbstractRollingUpgradeTestCase.java

@@ -8,8 +8,11 @@
 import java.nio.file.Path;
 import java.util.Locale;
 import java.util.Optional;
+import java.util.Set;
+
 import org.junit.Before;
 import org.opensearch.common.settings.Settings;
+import org.opensearch.ml.common.model.MLModelState;
 import org.opensearch.neuralsearch.BaseNeuralSearchIT;
 import static org.opensearch.neuralsearch.util.TestUtils.NEURAL_SEARCH_BWC_PREFIX;
 import static org.opensearch.neuralsearch.util.TestUtils.OLD_CLUSTER;
@@ -23,6 +26,8 @@
 
 public abstract class AbstractRollingUpgradeTestCase extends BaseNeuralSearchIT {
 
+    private static final Set<MLModelState> READY_FOR_INFERENCE_STATES = Set.of(MLModelState.LOADED, MLModelState.DEPLOYED);
+
     @Before
     protected String getIndexNameForTest() {
         // Creating index name by concatenating "neural-bwc-" prefix with test method name
@@ -159,4 +164,24 @@ protected void createPipelineForTextChunkingProcessor(String pipelineName) throw
         );
         createPipelineProcessor(requestBody, pipelineName, "", null);
     }
+
+    protected boolean isModelReadyForInference(final MLModelState mlModelState) throws Exception {
+        return READY_FOR_INFERENCE_STATES.contains(mlModelState);
+    }
+
+    protected void waitForModelToLoad(String modelId) throws Exception {
+        int maxAttempts = 30;  // Maximum number of attempts
+        int waitTimeInSeconds = 2;  // Time to wait between attempts
+
+        for (int attempt = 0; attempt < maxAttempts; attempt++) {
+            MLModelState state = getModelState(modelId);
+            if (isModelReadyForInference(state)) {
+                logger.info("Model {} is now loaded after {} attempts", modelId, attempt + 1);
+                return;
+            }
+            logger.info("Waiting for model {} to load. Current state: {}. Attempt {}/{}", modelId, state, attempt + 1, maxAttempts);
+            Thread.sleep(waitTimeInSeconds * 1000);
+        }
+        throw new RuntimeException("Model " + modelId + " failed to load after " + maxAttempts + " attempts");
+    }
 }

qa/rolling-upgrade/src/test/java/org/opensearch/neuralsearch/bwc/rolling/BatchIngestionIT.java

@@ -99,20 +99,4 @@ public void testBatchIngestion_SparseEncodingProcessor_E2EFlow() throws Exceptio
                 throw new IllegalStateException("Unexpected value: " + getClusterType());
         }
     }
-
-    private void waitForModelToLoad(String modelId) throws Exception {
-        int maxAttempts = 30;  // Maximum number of attempts
-        int waitTimeInSeconds = 2;  // Time to wait between attempts
-
-        for (int attempt = 0; attempt < maxAttempts; attempt++) {
-            MLModelState state = getModelState(modelId);
-            if (state == MLModelState.LOADED) {
-                logger.info("Model {} is now loaded after {} attempts", modelId, attempt + 1);
-                return;
-            }
-            logger.info("Waiting for model {} to load. Current state: {}. Attempt {}/{}", modelId, state, attempt + 1, maxAttempts);
-            Thread.sleep(waitTimeInSeconds * 1000);
-        }
-        throw new RuntimeException("Model " + modelId + " failed to load after " + maxAttempts + " attempts");
-    }
 }

src/main/java/org/opensearch/neuralsearch/plugin/NeuralSearch.java

@@ -14,7 +14,7 @@
 import java.util.Optional;
 import java.util.function.Supplier;
 
-import org.opensearch.client.Client;
+import org.opensearch.transport.client.Client;
 import org.opensearch.cluster.metadata.IndexNameExpressionResolver;
 import org.opensearch.cluster.service.ClusterService;
 import org.opensearch.common.settings.Setting;

src/main/java/org/opensearch/neuralsearch/processor/NormalizationProcessorWorkflow.java

@@ -242,7 +242,7 @@ private List<CompoundTopDocs> getCompoundTopDocs(CombineScoresDto combineScoresD
      * @return  max score
      */
     private float maxScoreForShard(CompoundTopDocs updatedTopDocs, boolean isSortEnabled) {
-        if (updatedTopDocs.getTotalHits().value == 0 || updatedTopDocs.getScoreDocs().isEmpty()) {
+        if (updatedTopDocs.getTotalHits().value() == 0 || updatedTopDocs.getScoreDocs().isEmpty()) {
             return MAX_SCORE_WHEN_NO_HITS_FOUND;
         }
         if (isSortEnabled) {

src/main/java/org/opensearch/neuralsearch/processor/combination/ScoreCombiner.java

@@ -81,7 +81,7 @@ private void combineShardScores(
         final CompoundTopDocs compoundQueryTopDocs,
         final Sort sort
     ) {
-        if (Objects.isNull(compoundQueryTopDocs) || compoundQueryTopDocs.getTotalHits().value == 0) {
+        if (Objects.isNull(compoundQueryTopDocs) || compoundQueryTopDocs.getTotalHits().value() == 0) {
             return;
         }
         List<TopDocs> topDocsPerSubQuery = compoundQueryTopDocs.getTopDocs();
@@ -292,7 +292,7 @@ private void updateQueryTopDocsWithCombinedScores(
         boolean isSortingEnabled
     ) {
         // - max number of hits will be the same which are passed from QueryPhase
-        long maxHits = compoundQueryTopDocs.getTotalHits().value;
+        long maxHits = compoundQueryTopDocs.getTotalHits().value();
         // - update query search results with normalized scores
         compoundQueryTopDocs.setScoreDocs(
             getCombinedScoreDocs(
@@ -309,7 +309,7 @@ private void updateQueryTopDocsWithCombinedScores(
 
     private TotalHits getTotalHits(final List<TopDocs> topDocsPerSubQuery, final long maxHits) {
         TotalHits.Relation totalHits = TotalHits.Relation.EQUAL_TO;
-        if (topDocsPerSubQuery.stream().anyMatch(topDocs -> topDocs.totalHits.relation == TotalHits.Relation.GREATER_THAN_OR_EQUAL_TO)) {
+        if (topDocsPerSubQuery.stream().anyMatch(topDocs -> topDocs.totalHits.relation() == TotalHits.Relation.GREATER_THAN_OR_EQUAL_TO)) {
             totalHits = TotalHits.Relation.GREATER_THAN_OR_EQUAL_TO;
         }
         return new TotalHits(maxHits, totalHits);
@@ -343,7 +343,7 @@ private List<ExplanationDetails> explainByShard(
         final CompoundTopDocs compoundQueryTopDocs,
         final Sort sort
     ) {
-        if (Objects.isNull(compoundQueryTopDocs) || compoundQueryTopDocs.getTotalHits().value == 0) {
+        if (Objects.isNull(compoundQueryTopDocs) || compoundQueryTopDocs.getTotalHits().value() == 0) {
             return List.of();
         }
         // create map of normalized scores results returned from the single shard

src/main/java/org/opensearch/neuralsearch/processor/rerank/RescoringRerankProcessor.java

@@ -59,7 +59,7 @@ public void rerank(
         final ActionListener<SearchResponse> listener
     ) {
         try {
-            if (searchResponse.getHits().getTotalHits().value == 0) {
+            if (searchResponse.getHits().getTotalHits().value() == 0) {
                 listener.onResponse(searchResponse);
                 return;
             }

src/main/java/org/opensearch/neuralsearch/query/HybridQuery.java

@@ -14,6 +14,7 @@
 import java.util.Map;
 import java.util.Objects;
 import java.util.concurrent.Callable;
+import java.util.stream.Collectors;
 
 import org.apache.lucene.search.BooleanClause;
 import org.apache.lucene.search.BooleanQuery;
@@ -42,6 +43,26 @@ public final class HybridQuery extends Query implements Iterable<Query> {
      * @param filterQueries list of filters that will be applied to each sub query. Each filter from the list is added as bool "filter" clause. If this is null sub queries will be executed as is
      */
     public HybridQuery(final Collection<Query> subQueries, final List<Query> filterQueries, final HybridQueryContext hybridQueryContext) {
+        this(
+            subQueries,
+            hybridQueryContext,
+            filterQueries == null
+                ? null
+                : filterQueries.stream().map(query -> new BooleanClause(query, BooleanClause.Occur.FILTER)).collect(Collectors.toList())
+        );
+    }
+
+    /**
+     * Create new instance of hybrid query object based on collection of sub queries and boolean clauses that are used as filters for each sub-query
+     * @param subQueries
+     * @param hybridQueryContext
+     * @param booleanClauses
+     */
+    public HybridQuery(
+        final Collection<Query> subQueries,
+        final HybridQueryContext hybridQueryContext,
+        final List<BooleanClause> booleanClauses
+    ) {
         Objects.requireNonNull(subQueries, "collection of queries must not be null");
         if (subQueries.isEmpty()) {
             throw new IllegalArgumentException("collection of queries must not be empty");
@@ -50,14 +71,14 @@ public HybridQuery(final Collection<Query> subQueries, final List<Query> filterQ
         if (Objects.nonNull(paginationDepth) && paginationDepth == 0) {
             throw new IllegalArgumentException("pagination_depth must not be zero");
         }
-        if (Objects.isNull(filterQueries) || filterQueries.isEmpty()) {
+        if (Objects.isNull(booleanClauses) || booleanClauses.isEmpty()) {
             this.subQueries = new ArrayList<>(subQueries);
         } else {
             List<Query> modifiedSubQueries = new ArrayList<>();
             for (Query subQuery : subQueries) {
                 BooleanQuery.Builder builder = new BooleanQuery.Builder();
                 builder.add(subQuery, BooleanClause.Occur.MUST);
-                filterQueries.forEach(filterQuery -> builder.add(filterQuery, BooleanClause.Occur.FILTER));
+                booleanClauses.forEach(filterQuery -> builder.add(booleanClauses));
                 modifiedSubQueries.add(builder.build());
             }
             this.subQueries = modifiedSubQueries;

src/main/java/org/opensearch/neuralsearch/query/HybridQueryScorer.java

@@ -49,7 +49,7 @@ public HybridQueryScorer(final Weight weight, final List<Scorer> subScorers) thr
     }
 
     HybridQueryScorer(final Weight weight, final List<Scorer> subScorers, final ScoreMode scoreMode) throws IOException {
-        super(weight);
+        super();
         this.subScorers = Collections.unmodifiableList(subScorers);
         this.numSubqueries = subScorers.size();
         this.subScorersPQ = initializeSubScorersPQ();

src/main/java/org/opensearch/neuralsearch/query/HybridQueryWeight.java

@@ -109,24 +109,6 @@ private Void addScoreSupplier(Weight weight, HybridQueryExecutorCollector<LeafRe
         return null;
     }
 
-    /**
-     * Create the scorer used to score our associated Query
-     *
-     * @param context the {@link LeafReaderContext} for which to return the
-     *                {@link Scorer}.
-     * @return scorer of hybrid query that contains scorers of each sub-query, null if there are no matches in any sub-query
-     * @throws IOException
-     */
-    @Override
-    public Scorer scorer(LeafReaderContext context) throws IOException {
-        ScorerSupplier supplier = scorerSupplier(context);
-        if (supplier == null) {
-            return null;
-        }
-        supplier.setTopLevelScoringClause();
-        return supplier.get(Long.MAX_VALUE);
-    }
-
     /**
      * Check if weight object can be cached
      *

src/main/java/org/opensearch/neuralsearch/query/NeuralKNNQuery.java

@@ -5,7 +5,6 @@
 package org.opensearch.neuralsearch.query;
 
 import lombok.Getter;
-import org.apache.lucene.index.IndexReader;
 import org.apache.lucene.search.IndexSearcher;
 import org.apache.lucene.search.Query;
 import org.apache.lucene.search.QueryVisitor;
@@ -45,8 +44,8 @@ public Weight createWeight(IndexSearcher searcher, ScoreMode scoreMode, float bo
     }
 
     @Override
-    public Query rewrite(IndexReader reader) throws IOException {
-        Query rewritten = knnQuery.rewrite(reader);
+    public Query rewrite(IndexSearcher indexSearcher) throws IOException {
+        Query rewritten = knnQuery.rewrite(indexSearcher);
         if (rewritten == knnQuery) {
             return this;
         }

src/main/java/org/opensearch/neuralsearch/query/NeuralSparseQueryBuilder.java

@@ -21,7 +21,7 @@
 import org.apache.lucene.search.BooleanQuery;
 import org.apache.lucene.search.Query;
 import org.opensearch.Version;
-import org.opensearch.client.Client;
+import org.opensearch.transport.client.Client;
 import org.opensearch.common.SetOnce;
 import org.opensearch.common.collect.Tuple;
 import org.opensearch.core.ParseField;

src/main/java/org/opensearch/neuralsearch/search/HybridDisiWrapper.java

@@ -17,7 +17,7 @@ public class HybridDisiWrapper extends DisiWrapper {
     private final int subQueryIndex;
 
     public HybridDisiWrapper(Scorer scorer, int subQueryIndex) {
-        super(scorer);
+        super(scorer, false);
         this.subQueryIndex = subQueryIndex;
     }
 }

src/main/java/org/opensearch/neuralsearch/search/collector/HybridTopFieldDocSortCollector.java

@@ -166,13 +166,13 @@ private HybridQueryScorer getHybridQueryScorer(final Scorable scorer) throws IOE
                 return (HybridQueryScorer) scorer;
             }
             for (Scorable.ChildScorable childScorable : scorer.getChildren()) {
-                HybridQueryScorer hybridQueryScorer = getHybridQueryScorer(childScorable.child);
+                HybridQueryScorer hybridQueryScorer = getHybridQueryScorer(childScorable.child());
                 if (Objects.nonNull(hybridQueryScorer)) {
                     log.debug(
                         String.format(
                             Locale.ROOT,
                             "found hybrid query scorer, it's child of scorer %s",
-                            childScorable.child.getClass().getSimpleName()
+                            childScorable.child().getClass().getSimpleName()
                         )
                     );
                     return hybridQueryScorer;
@@ -289,7 +289,7 @@ private void initializeLeafFieldComparators(LeafReaderContext context, int subQu
         private void initializeComparators(LeafReaderContext context, int subQueryNumber) throws IOException {
             // as all segments are sorted in the same way, enough to check only the 1st segment for indexSort
             if (searchSortPartOfIndexSort == null) {
-                Sort indexSort = context.reader().getMetaData().getSort();
+                Sort indexSort = context.reader().getMetaData().sort();
                 searchSortPartOfIndexSort = canEarlyTerminate(sort, indexSort);
                 if (searchSortPartOfIndexSort) {
                     firstComparator.disableSkipping();