LUCENE-10606: For KnnVectorQuery, optimize case where filter is backed by BitSetIterator (#951)

Instead of collecting hit-by-hit using a `LeafCollector`, we break down the
search by instantiating a weight, creating scorers, and checking the underlying
iterator. If it is backed by a `BitSet`, we directly update the reference (as
we won't be editing the `Bits`). Else we can create a new `BitSet` from the
iterator using `BitSet.of`.

lucene/CHANGES.txt

@@ -105,6 +105,8 @@ Optimizations
 
 * LUCENE-10618: Implement BooleanQuery rewrite rules based for minimumShouldMatch. (Fang Hou)
 
+* LUCENE-10606: For KnnVectorQuery, optimize case where filter is backed by BitSetIterator (Kaival Parikh)
+
 Bug Fixes
 ---------------------
 

lucene/core/src/java/org/apache/lucene/search/KnnVectorQuery.java

@@ -32,7 +32,6 @@ import org.apache.lucene.index.VectorValues;
 import org.apache.lucene.util.BitSet;
 import org.apache.lucene.util.BitSetIterator;
 import org.apache.lucene.util.Bits;
-import org.apache.lucene.util.FixedBitSet;
 
 /**
  * Uses {@link KnnVectorsReader#search} to perform nearest neighbour search.
@@ -92,20 +91,20 @@ public class KnnVectorQuery extends Query {
   public Query rewrite(IndexReader reader) throws IOException {
     TopDocs[] perLeafResults = new TopDocs[reader.leaves().size()];
 
-    BitSetCollector filterCollector = null;
+    Weight filterWeight = null;
     if (filter != null) {
-      filterCollector = new BitSetCollector(reader.leaves().size());
       IndexSearcher indexSearcher = new IndexSearcher(reader);
       BooleanQuery booleanQuery =
           new BooleanQuery.Builder()
               .add(filter, BooleanClause.Occur.FILTER)
               .add(new FieldExistsQuery(field), BooleanClause.Occur.FILTER)
               .build();
-      indexSearcher.search(booleanQuery, filterCollector);
+      Query rewritten = indexSearcher.rewrite(booleanQuery);
+      filterWeight = indexSearcher.createWeight(rewritten, ScoreMode.COMPLETE_NO_SCORES, 1f);
     }
 
     for (LeafReaderContext ctx : reader.leaves()) {
-      TopDocs results = searchLeaf(ctx, filterCollector);
+      TopDocs results = searchLeaf(ctx, filterWeight);
       if (ctx.docBase > 0) {
         for (ScoreDoc scoreDoc : results.scoreDocs) {
           scoreDoc.doc += ctx.docBase;
@@ -121,18 +120,22 @@ public class KnnVectorQuery extends Query {
     return createRewrittenQuery(reader, topK);
   }
 
-  private TopDocs searchLeaf(LeafReaderContext ctx, BitSetCollector filterCollector)
+  private TopDocs searchLeaf(LeafReaderContext ctx, Weight filterWeight) throws IOException {
-      throws IOException {
+    Bits liveDocs = ctx.reader().getLiveDocs();
+    int maxDoc = ctx.reader().maxDoc();
 
-    if (filterCollector == null) {
+    if (filterWeight == null) {
-      Bits acceptDocs = ctx.reader().getLiveDocs();
+      return approximateSearch(ctx, liveDocs, Integer.MAX_VALUE);
-      return approximateSearch(ctx, acceptDocs, Integer.MAX_VALUE);
+    }
-    } else {
+
-      BitSetIterator filterIterator = filterCollector.getIterator(ctx.ord);
+    Scorer scorer = filterWeight.scorer(ctx);
-      if (filterIterator == null || filterIterator.cost() == 0) {
+    if (scorer == null) {
       return NO_RESULTS;
     }
 
+    BitSet bitSet = createBitSet(scorer.iterator(), liveDocs, maxDoc);
+    BitSetIterator filterIterator = new BitSetIterator(bitSet, bitSet.cardinality());
+
     if (filterIterator.cost() <= k) {
       // If there are <= k possible matches, short-circuit and perform exact search, since HNSW
       // must always visit at least k documents
@@ -140,10 +143,7 @@ public class KnnVectorQuery extends Query {
     }
 
     // Perform the approximate kNN search
-      Bits acceptDocs =
+    TopDocs results = approximateSearch(ctx, bitSet, (int) filterIterator.cost());
-          filterIterator.getBitSet(); // The filter iterator already incorporates live docs
-      int visitedLimit = (int) filterIterator.cost();
-      TopDocs results = approximateSearch(ctx, acceptDocs, visitedLimit);
     if (results.totalHits.relation == TotalHits.Relation.EQUAL_TO) {
       return results;
     } else {
@@ -151,6 +151,23 @@ public class KnnVectorQuery extends Query {
       return exactSearch(ctx, filterIterator);
     }
   }
+
+  private BitSet createBitSet(DocIdSetIterator iterator, Bits liveDocs, int maxDoc)
+      throws IOException {
+    if (liveDocs == null && iterator instanceof BitSetIterator bitSetIterator) {
+      // If we already have a BitSet and no deletions, reuse the BitSet
+      return bitSetIterator.getBitSet();
+    } else {
+      // Create a new BitSet from matching and live docs
+      FilteredDocIdSetIterator filterIterator =
+          new FilteredDocIdSetIterator(iterator) {
+            @Override
+            protected boolean match(int doc) {
+              return liveDocs == null || liveDocs.get(doc);
+            }
+          };
+      return BitSet.of(filterIterator, maxDoc);
+    }
   }
 
   private TopDocs approximateSearch(LeafReaderContext context, Bits acceptDocs, int visitedLimit)
@@ -202,47 +219,6 @@ public class KnnVectorQuery extends Query {
     return new TopDocs(totalHits, topScoreDocs);
   }
 
-  private static class BitSetCollector extends SimpleCollector {
-
-    private final BitSet[] bitSets;
-    private final int[] cost;
-    private int ord;
-
-    private BitSetCollector(int numLeaves) {
-      this.bitSets = new BitSet[numLeaves];
-      this.cost = new int[bitSets.length];
-    }
-
-    /**
-     * Return an iterator whose {@link BitSet} contains the matching documents, and whose {@link
-     * BitSetIterator#cost()} is the exact cardinality. If the leaf was never visited, then return
-     * null.
-     */
-    public BitSetIterator getIterator(int contextOrd) {
-      if (bitSets[contextOrd] == null) {
-        return null;
-      }
-      return new BitSetIterator(bitSets[contextOrd], cost[contextOrd]);
-    }
-
-    @Override
-    public void collect(int doc) throws IOException {
-      bitSets[ord].set(doc);
-      cost[ord]++;
-    }
-
-    @Override
-    protected void doSetNextReader(LeafReaderContext context) throws IOException {
-      bitSets[context.ord] = new FixedBitSet(context.reader().maxDoc());
-      ord = context.ord;
-    }
-
-    @Override
-    public org.apache.lucene.search.ScoreMode scoreMode() {
-      return org.apache.lucene.search.ScoreMode.COMPLETE_NO_SCORES;
-    }
-  }
-
   private Query createRewrittenQuery(IndexReader reader, TopDocs topK) {
     int len = topK.scoreDocs.length;
     Arrays.sort(topK.scoreDocs, Comparator.comparingInt(a -> a.doc));

lucene/core/src/test/org/apache/lucene/search/TestKnnVectorQuery.java

@@ -45,7 +45,10 @@ import org.apache.lucene.store.Directory;
 import org.apache.lucene.tests.index.RandomIndexWriter;
 import org.apache.lucene.tests.util.LuceneTestCase;
 import org.apache.lucene.tests.util.TestUtil;
+import org.apache.lucene.util.BitSet;
+import org.apache.lucene.util.BitSetIterator;
 import org.apache.lucene.util.Bits;
+import org.apache.lucene.util.FixedBitSet;
 import org.apache.lucene.util.VectorUtil;
 
 /** TestKnnVectorQuery tests KnnVectorQuery. */
@@ -699,6 +702,36 @@ public class TestKnnVectorQuery extends LuceneTestCase {
     }
   }
 
+  /**
+   * Test that KnnVectorQuery optimizes the case where the filter query is backed by {@link
+   * BitSetIterator}.
+   */
+  public void testBitSetQuery() throws IOException {
+    IndexWriterConfig iwc = newIndexWriterConfig();
+    try (Directory dir = newDirectory();
+        IndexWriter w = new IndexWriter(dir, iwc)) {
+      final int numDocs = 100;
+      final int dim = 30;
+      for (int i = 0; i < numDocs; ++i) {
+        Document d = new Document();
+        d.add(new KnnVectorField("vector", randomVector(dim)));
+        w.addDocument(d);
+      }
+      w.commit();
+
+      try (DirectoryReader reader = DirectoryReader.open(dir)) {
+        IndexSearcher searcher = new IndexSearcher(reader);
+
+        Query filter = new ThrowingBitSetQuery(new FixedBitSet(numDocs));
+        expectThrows(
+            UnsupportedOperationException.class,
+            () ->
+                searcher.search(
+                    new KnnVectorQuery("vector", randomVector(dim), 10, filter), numDocs));
+      }
+    }
+  }
+
   /** Creates a new directory and adds documents with the given vectors as kNN vector fields */
   private Directory getIndexStore(String field, float[]... contents) throws IOException {
     Directory indexStore = newDirectory();
@@ -797,4 +830,54 @@ public class TestKnnVectorQuery extends LuceneTestCase {
       return in.getCoreCacheHelper();
     }
   }
+
+  private static class ThrowingBitSetQuery extends Query {
+
+    private final FixedBitSet docs;
+
+    ThrowingBitSetQuery(FixedBitSet docs) {
+      this.docs = docs;
+    }
+
+    @Override
+    public Weight createWeight(IndexSearcher searcher, ScoreMode scoreMode, float boost)
+        throws IOException {
+      return new ConstantScoreWeight(this, boost) {
+        @Override
+        public Scorer scorer(LeafReaderContext context) throws IOException {
+          BitSetIterator bitSetIterator =
+              new BitSetIterator(docs, docs.approximateCardinality()) {
+                @Override
+                public BitSet getBitSet() {
+                  throw new UnsupportedOperationException("reusing BitSet is not supported");
+                }
+              };
+          return new ConstantScoreScorer(this, score(), scoreMode, bitSetIterator);
+        }
+
+        @Override
+        public boolean isCacheable(LeafReaderContext ctx) {
+          return false;
+        }
+      };
+    }
+
+    @Override
+    public void visit(QueryVisitor visitor) {}
+
+    @Override
+    public String toString(String field) {
+      return "throwingBitSetQuery";
+    }
+
+    @Override
+    public boolean equals(Object other) {
+      return sameClassAs(other) && docs.equals(((ThrowingBitSetQuery) other).docs);
+    }
+
+    @Override
+    public int hashCode() {
+      return 31 * classHash() + docs.hashCode();
+    }
+  }
 }