Control the auto-adjustment of targetHits in ANN using post-filtering.

When searching the HNSW index in a post-filtering case,
targetHits is auto-adjusted in an effort to still expose targetHits hits to first-phase ranking after post-filtering.
The following formula is now used to ensure an upper bound of adjustedTargetHits,
avoiding that the search in the HNSW index takes too long.

adjustedTargetHits = min(targetHits / estimatedHitRatio, targetHits * targetHitsMaxAdjustmentFactor).

The target-hits-max-adjustment-factor can be set in a rank profile and overriden per query.
The value is in the range [1.0,inf], with the default being 20.0.

When setting this to 1.0, auto-adjustment of targetHits is effectively disabled.

23 files changed, 212 insertions, 48 deletions

diff --git a/config-model/src/main/java/com/yahoo/schema/RankProfile.java b/config-model/src/main/java/com/yahoo/schema/RankProfile.java
index 69f32daef4a..35ef12f077a 100644
--- a/config-model/src/main/java/com/yahoo/schema/RankProfile.java
+++ b/config-model/src/main/java/com/yahoo/schema/RankProfile.java
@@ -100,6 +100,7 @@ public class RankProfile implements Cloneable {
     private Double termwiseLimit = null;
     private Double postFilterThreshold = null;
     private Double approximateThreshold = null;
+    private Double targetHitsMaxAdjustmentFactor = null;
 
     /** The drop limit used to drop hits with rank score less than or equal to this value */
     private double rankScoreDropLimit = -Double.MAX_VALUE;
@@ -768,6 +769,7 @@ public class RankProfile implements Cloneable {
     public void setTermwiseLimit(double termwiseLimit) { this.termwiseLimit = termwiseLimit; }
     public void setPostFilterThreshold(double threshold) { this.postFilterThreshold = threshold; }
     public void setApproximateThreshold(double threshold) { this.approximateThreshold = threshold; }
+    public void setTargetHitsMaxAdjustmentFactor(double factor) { this.targetHitsMaxAdjustmentFactor = factor; }
 
     public OptionalDouble getTermwiseLimit() {
         if (termwiseLimit != null) return OptionalDouble.of(termwiseLimit);
@@ -789,6 +791,13 @@ public class RankProfile implements Cloneable {
         return uniquelyInherited(p -> p.getApproximateThreshold(), l -> l.isPresent(), "approximate-threshold").orElse(OptionalDouble.empty());
     }
 
+    public OptionalDouble getTargetHitsMaxAdjustmentFactor() {
+        if (targetHitsMaxAdjustmentFactor != null) {
+            return OptionalDouble.of(targetHitsMaxAdjustmentFactor);
+        }
+        return uniquelyInherited(p -> p.getTargetHitsMaxAdjustmentFactor(), l -> l.isPresent(), "target-hits-max-adjustment-factor").orElse(OptionalDouble.empty());
+    }
+
     /** Whether we should ignore the default rank features. Set to null to use inherited */
     public void setIgnoreDefaultRankFeatures(Boolean ignoreDefaultRankFeatures) {
         this.ignoreDefaultRankFeatures = ignoreDefaultRankFeatures;
diff --git a/config-model/src/main/java/com/yahoo/schema/derived/RawRankProfile.java b/config-model/src/main/java/com/yahoo/schema/derived/RawRankProfile.java
index 82c0c9d516a..29bd454cc62 100644
--- a/config-model/src/main/java/com/yahoo/schema/derived/RawRankProfile.java
+++ b/config-model/src/main/java/com/yahoo/schema/derived/RawRankProfile.java
@@ -153,6 +153,7 @@ public class RawRankProfile implements RankProfilesConfig.Producer {
         private final double termwiseLimit;
         private final OptionalDouble postFilterThreshold;
         private final OptionalDouble approximateThreshold;
+        private final OptionalDouble targetHitsMaxAdjustmentFactor;
         private final double rankScoreDropLimit;
         private final boolean enableNestedMultivalueGrouping;
 
@@ -197,6 +198,7 @@ public class RawRankProfile implements RankProfilesConfig.Producer {
             enableNestedMultivalueGrouping = deployProperties.featureFlags().enableNestedMultivalueGrouping();
             postFilterThreshold = compiled.getPostFilterThreshold();
             approximateThreshold = compiled.getApproximateThreshold();
+            targetHitsMaxAdjustmentFactor = compiled.getTargetHitsMaxAdjustmentFactor();
             keepRankCount = compiled.getKeepRankCount();
             rankScoreDropLimit = compiled.getRankScoreDropLimit();
             ignoreDefaultRankFeatures = compiled.getIgnoreDefaultRankFeatures();
@@ -429,6 +431,9 @@ public class RawRankProfile implements RankProfilesConfig.Producer {
             if (approximateThreshold.isPresent()) {
                 properties.add(new Pair<>("vespa.matching.global_filter.lower_limit", String.valueOf(approximateThreshold.getAsDouble())));
             }
+            if (targetHitsMaxAdjustmentFactor.isPresent()) {
+                properties.add(new Pair<>("vespa.matching.nns.target_hits_max_adjustment_factor", String.valueOf(targetHitsMaxAdjustmentFactor.getAsDouble())));
+            }
             if (matchPhaseSettings != null) {
                 properties.add(new Pair<>("vespa.matchphase.degradation.attribute", matchPhaseSettings.getAttribute()));
                 properties.add(new Pair<>("vespa.matchphase.degradation.ascendingorder", matchPhaseSettings.getAscending() + ""));
diff --git a/config-model/src/main/java/com/yahoo/schema/parser/ConvertParsedRanking.java b/config-model/src/main/java/com/yahoo/schema/parser/ConvertParsedRanking.java
index bdecf6332a0..c25d393c8bf 100644
--- a/config-model/src/main/java/com/yahoo/schema/parser/ConvertParsedRanking.java
+++ b/config-model/src/main/java/com/yahoo/schema/parser/ConvertParsedRanking.java
@@ -65,6 +65,8 @@ public class ConvertParsedRanking {
                 (value -> profile.setPostFilterThreshold(value));
         parsed.getApproximateThreshold().ifPresent
                 (value -> profile.setApproximateThreshold(value));
+        parsed.getTargetHitsMaxAdjustmentFactor().ifPresent
+                (value -> profile.setTargetHitsMaxAdjustmentFactor(value));
         parsed.getKeepRankCount().ifPresent
             (value -> profile.setKeepRankCount(value));
         parsed.getMinHitsPerThread().ifPresent
diff --git a/config-model/src/main/java/com/yahoo/schema/parser/ParsedRankProfile.java b/config-model/src/main/java/com/yahoo/schema/parser/ParsedRankProfile.java
index 2809ee0c633..1d06b993cdc 100644
--- a/config-model/src/main/java/com/yahoo/schema/parser/ParsedRankProfile.java
+++ b/config-model/src/main/java/com/yahoo/schema/parser/ParsedRankProfile.java
@@ -29,6 +29,7 @@ class ParsedRankProfile extends ParsedBlock {
     private Double termwiseLimit = null;
     private Double postFilterThreshold = null;
     private Double approximateThreshold = null;
+    private Double targetHitsMaxAdjustmentFactor = null;
     private final List<FeatureList> matchFeatures = new ArrayList<>();
     private final List<FeatureList> rankFeatures = new ArrayList<>();
     private final List<FeatureList> summaryFeatures = new ArrayList<>();
@@ -65,6 +66,7 @@ class ParsedRankProfile extends ParsedBlock {
     Optional<Double> getTermwiseLimit() { return Optional.ofNullable(this.termwiseLimit); }
     Optional<Double> getPostFilterThreshold() { return Optional.ofNullable(this.postFilterThreshold); }
     Optional<Double> getApproximateThreshold() { return Optional.ofNullable(this.approximateThreshold); }
+    Optional<Double> getTargetHitsMaxAdjustmentFactor() { return Optional.ofNullable(this.targetHitsMaxAdjustmentFactor); }
     List<FeatureList> getMatchFeatures() { return List.copyOf(this.matchFeatures); }
     List<FeatureList> getRankFeatures() { return List.copyOf(this.rankFeatures); }
     List<FeatureList> getSummaryFeatures() { return List.copyOf(this.summaryFeatures); }
@@ -231,4 +233,9 @@ class ParsedRankProfile extends ParsedBlock {
         this.approximateThreshold = threshold;
     }
 
+    void setTargetHitsMaxAdjustmentFactor(double factor) {
+        verifyThat(targetHitsMaxAdjustmentFactor == null, "already has target-hits-max-adjustment-factor");
+        this.targetHitsMaxAdjustmentFactor = factor;
+    }
+
 }
diff --git a/config-model/src/main/javacc/SchemaParser.jj b/config-model/src/main/javacc/SchemaParser.jj
index b2cb258c0ab..42eeabb5ac7 100644
--- a/config-model/src/main/javacc/SchemaParser.jj
+++ b/config-model/src/main/javacc/SchemaParser.jj
@@ -326,6 +326,7 @@ TOKEN :
 | < TERMWISE_LIMIT: "termwise-limit" >
 | < POST_FILTER_THRESHOLD: "post-filter-threshold" >
 | < APPROXIMATE_THRESHOLD: "approximate-threshold" >
+| < TARGET_HITS_MAX_ADJUSTMENT_FACTOR: "target-hits-max-adjustment-factor" >
 | < KEEP_RANK_COUNT: "keep-rank-count" >
 | < RANK_SCORE_DROP_LIMIT: "rank-score-drop-limit" >
 | < CONSTANTS: "constants" >
@@ -1727,6 +1728,7 @@ void rankProfileItem(ParsedSchema schema, ParsedRankProfile profile) : { }
       | termwiseLimit(profile)
       | postFilterThreshold(profile)
       | approximateThreshold(profile)
+      | targetHitsMaxAdjustmentFactor(profile)
       | rankFeatures(profile)
       | rankProperties(profile)
       | secondPhase(profile)
@@ -2190,6 +2192,19 @@ void approximateThreshold(ParsedRankProfile profile) :
 }
 
 /**
+ * This rule consumes a target-hits-max-adjustment-factor statement for a rank profile.
+ *
+ * @param profile the rank profile to modify
+ */
+void targetHitsMaxAdjustmentFactor(ParsedRankProfile profile) :
+{
+    double factor;
+}
+{
+    (<TARGET_HITS_MAX_ADJUSTMENT_FACTOR> <COLON> factor = floatValue()) { profile.setTargetHitsMaxAdjustmentFactor(factor); }
+}
+
+/**
  * Consumes a rank-properties block of a rank profile. There
  * is a little trick within this rule to allow the final rank property
  * to skip the terminating newline token.
@@ -2641,6 +2656,7 @@ String identifierWithDash() :
     | <SECOND_PHASE>
     | <STRUCT_FIELD>
     | <SUMMARY_TO>
+    | <TARGET_HITS_MAX_ADJUSTMENT_FACTOR>
     | <TERMWISE_LIMIT>
     | <UPPER_BOUND>
     ) { return token.image; }
diff --git a/config-model/src/test/java/com/yahoo/schema/RankProfileTestCase.java b/config-model/src/test/java/com/yahoo/schema/RankProfileTestCase.java
index 85225f0d255..380b458ea8c 100644
--- a/config-model/src/test/java/com/yahoo/schema/RankProfileTestCase.java
+++ b/config-model/src/test/java/com/yahoo/schema/RankProfileTestCase.java
@@ -459,17 +459,9 @@ public class RankProfileTestCase extends AbstractSchemaTestCase {
     }
 
     private void verifyApproximateNearestNeighborThresholdSettings(Double postFilterThreshold, Double approximateThreshold) throws ParseException {
-        var rankProfileRegistry = new RankProfileRegistry();
-        var props = new TestProperties();
-        var queryProfileRegistry = new QueryProfileRegistry();
-        var builder = new ApplicationBuilder(rankProfileRegistry, queryProfileRegistry, props);
-        builder.addSchema(createSDWithRankProfileThresholds(postFilterThreshold, approximateThreshold));
-        builder.build(true);
-
-        var schema = builder.getSchema();
-        var rankProfile = rankProfileRegistry.get(schema, "my_profile");
-        var rawRankProfile = new RawRankProfile(rankProfile, new LargeRankingExpressions(new MockFileRegistry()), queryProfileRegistry,
-                                                new ImportedMlModels(), new AttributeFields(schema), props);
+        var rp = createRankProfile(postFilterThreshold, approximateThreshold, null);
+        var rankProfile = rp.getFirst();
+        var rawRankProfile = rp.getSecond();
 
         if (postFilterThreshold != null) {
             assertEquals((double)postFilterThreshold, rankProfile.getPostFilterThreshold().getAsDouble(), 0.000001);
@@ -488,13 +480,52 @@ public class RankProfileTestCase extends AbstractSchemaTestCase {
         }
     }
 
-    private String createSDWithRankProfileThresholds(Double postFilterThreshold, Double approximateThreshold) {
+    @Test
+    void target_hits_max_adjustment_factor_is_configurable() throws ParseException {
+        verifyTargetHitsMaxAdjustmentFactor(null);
+        verifyTargetHitsMaxAdjustmentFactor(2.0);
+    }
+
+    private void verifyTargetHitsMaxAdjustmentFactor(Double targetHitsMaxAdjustmentFactor) throws ParseException {
+        var rp = createRankProfile(null, null, targetHitsMaxAdjustmentFactor);
+        var rankProfile = rp.getFirst();
+        var rawRankProfile = rp.getSecond();
+        if (targetHitsMaxAdjustmentFactor != null) {
+            assertEquals((double)targetHitsMaxAdjustmentFactor, rankProfile.getTargetHitsMaxAdjustmentFactor().getAsDouble(), 0.000001);
+            assertEquals(String.valueOf(targetHitsMaxAdjustmentFactor), findProperty(rawRankProfile.configProperties(), "vespa.matching.nns.target_hits_max_adjustment_factor").get());
+        } else {
+            assertTrue(rankProfile.getTargetHitsMaxAdjustmentFactor().isEmpty());
+            assertFalse(findProperty(rawRankProfile.configProperties(), "vespa.matching.nns.target_hits_max_adjustment_factor").isPresent());
+        }
+    }
+
+    private Pair<RankProfile, RawRankProfile> createRankProfile(Double postFilterThreshold,
+                                                                Double approximateThreshold,
+                                                                Double targetHitsMaxAdjustmentFactor) throws ParseException {
+        var rankProfileRegistry = new RankProfileRegistry();
+        var props = new TestProperties();
+        var queryProfileRegistry = new QueryProfileRegistry();
+        var builder = new ApplicationBuilder(rankProfileRegistry, queryProfileRegistry, props);
+        builder.addSchema(createSDWithRankProfile(postFilterThreshold, approximateThreshold, targetHitsMaxAdjustmentFactor));
+        builder.build(true);
+
+        var schema = builder.getSchema();
+        var rankProfile = rankProfileRegistry.get(schema, "my_profile");
+        var rawRankProfile = new RawRankProfile(rankProfile, new LargeRankingExpressions(new MockFileRegistry()), queryProfileRegistry,
+                new ImportedMlModels(), new AttributeFields(schema), props);
+        return new Pair<>(rankProfile, rawRankProfile);
+    }
+
+    private String createSDWithRankProfile(Double postFilterThreshold,
+                                           Double approximateThreshold,
+                                           Double targetHitsMaxAdjustmentFactor) {
         return joinLines(
                 "search test {",
                 "    document test {}",
                 "    rank-profile my_profile {",
-                (postFilterThreshold != null ? ("        post-filter-threshold: " + postFilterThreshold) : ""),
-                (approximateThreshold != null ? ("        approximate-threshold: " + approximateThreshold) : ""),
+                (postFilterThreshold != null ?           ("        post-filter-threshold: " + postFilterThreshold) : ""),
+                (approximateThreshold != null ?          ("        approximate-threshold: " + approximateThreshold) : ""),
+                (targetHitsMaxAdjustmentFactor != null ? ("        target-hits-max-adjustment-factor: " + targetHitsMaxAdjustmentFactor) : ""),
                 "    }",
                 "}");
     }
diff --git a/container-search/abi-spec.json b/container-search/abi-spec.json
index 0f440957dfd..cdb660f294a 100644
--- a/container-search/abi-spec.json
+++ b/container-search/abi-spec.json
@@ -6981,12 +6981,14 @@
       "public java.lang.Integer getMinHitsPerThread()",
       "public java.lang.Double getPostFilterThreshold()",
       "public java.lang.Double getApproximateThreshold()",
+      "public java.lang.Double getTargetHitsMaxAdjustmentFactor()",
       "public void setTermwiselimit(double)",
       "public void setNumThreadsPerSearch(int)",
       "public void setNumSearchPartitions(int)",
       "public void setMinHitsPerThread(int)",
       "public void setPostFilterThreshold(double)",
       "public void setApproximateThreshold(double)",
+      "public void setTargetHitsMaxAdjustmentFactor(double)",
       "public void prepare(com.yahoo.search.query.ranking.RankProperties)",
       "public com.yahoo.search.query.ranking.Matching clone()",
       "public boolean equals(java.lang.Object)",
@@ -7000,6 +7002,7 @@
       "public static final java.lang.String MINHITSPERTHREAD",
       "public static final java.lang.String POST_FILTER_THRESHOLD",
       "public static final java.lang.String APPROXIMATE_THRESHOLD",
+      "public static final java.lang.String TARGET_HITS_MAX_ADJUSTMENT_FACTOR",
       "public java.lang.Double termwiseLimit"
     ]
   },
diff --git a/container-search/src/main/java/com/yahoo/search/query/properties/QueryProperties.java b/container-search/src/main/java/com/yahoo/search/query/properties/QueryProperties.java
index 800b3a1ba89..99d6959441a 100644
--- a/container-search/src/main/java/com/yahoo/search/query/properties/QueryProperties.java
+++ b/container-search/src/main/java/com/yahoo/search/query/properties/QueryProperties.java
@@ -91,6 +91,7 @@ public class QueryProperties extends Properties {
         addDualCasedRM(map, Matching.MINHITSPERTHREAD, GetterSetter.of(query -> query.getRanking().getMatching().getMinHitsPerThread(), (query, value) -> query.getRanking().getMatching().setMinHitsPerThread(asInteger(value, 0))));
         addDualCasedRM(map, Matching.POST_FILTER_THRESHOLD, GetterSetter.of(query -> query.getRanking().getMatching().getPostFilterThreshold(), (query, value) -> query.getRanking().getMatching().setPostFilterThreshold(asDouble(value, 1.0))));
         addDualCasedRM(map, Matching.APPROXIMATE_THRESHOLD, GetterSetter.of(query -> query.getRanking().getMatching().getApproximateThreshold(), (query, value) -> query.getRanking().getMatching().setApproximateThreshold(asDouble(value, 0.05))));
+        addDualCasedRM(map, Matching.TARGET_HITS_MAX_ADJUSTMENT_FACTOR, GetterSetter.of(query -> query.getRanking().getMatching().getTargetHitsMaxAdjustmentFactor(), (query, value) -> query.getRanking().getMatching().setTargetHitsMaxAdjustmentFactor(asDouble(value, 20.0))));
 
         map.put(CompoundName.fromComponents(Ranking.RANKING, Ranking.MATCH_PHASE, MatchPhase.ATTRIBUTE), GetterSetter.of(query -> query.getRanking().getMatchPhase().getAttribute(), (query, value) -> query.getRanking().getMatchPhase().setAttribute(asString(value, null))));
         map.put(CompoundName.fromComponents(Ranking.RANKING, Ranking.MATCH_PHASE, MatchPhase.ASCENDING), GetterSetter.of(query -> query.getRanking().getMatchPhase().getAscending(), (query, value) -> query.getRanking().getMatchPhase().setAscending(asBoolean(value, false))));
diff --git a/container-search/src/main/java/com/yahoo/search/query/ranking/Matching.java b/container-search/src/main/java/com/yahoo/search/query/ranking/Matching.java
index 35fbd52f967..4d21f32d16d 100644
--- a/container-search/src/main/java/com/yahoo/search/query/ranking/Matching.java
+++ b/container-search/src/main/java/com/yahoo/search/query/ranking/Matching.java
@@ -24,6 +24,7 @@ public class Matching implements Cloneable {
     public static final String MINHITSPERTHREAD = "minHitsPerThread";
     public static final String POST_FILTER_THRESHOLD = "postFilterThreshold";
     public static final String APPROXIMATE_THRESHOLD = "approximateThreshold";
+    public static final String TARGET_HITS_MAX_ADJUSTMENT_FACTOR = "targetHitsMaxAdjustmentFactor";
 
     static {
         argumentType =new QueryProfileType(Ranking.MATCHING);
@@ -35,6 +36,7 @@ public class Matching implements Cloneable {
         argumentType.addField(new FieldDescription(MINHITSPERTHREAD, "integer"));
         argumentType.addField(new FieldDescription(POST_FILTER_THRESHOLD, "double"));
         argumentType.addField(new FieldDescription(APPROXIMATE_THRESHOLD, "double"));
+        argumentType.addField(new FieldDescription(TARGET_HITS_MAX_ADJUSTMENT_FACTOR, "double"));
         argumentType.freeze();
     }
 
@@ -46,6 +48,7 @@ public class Matching implements Cloneable {
     private Integer minHitsPerThread = null;
     private Double postFilterThreshold = null;
     private Double approximateThreshold = null;
+    private Double targetHitsMaxAdjustmentFactor = null;
 
     public Double getTermwiseLimit() { return termwiseLimit; }
     public Integer getNumThreadsPerSearch() { return numThreadsPerSearch; }
@@ -53,6 +56,7 @@ public class Matching implements Cloneable {
     public Integer getMinHitsPerThread() { return minHitsPerThread; }
     public Double getPostFilterThreshold() { return postFilterThreshold; }
     public Double getApproximateThreshold() { return approximateThreshold; }
+    public Double getTargetHitsMaxAdjustmentFactor() { return targetHitsMaxAdjustmentFactor; }
 
     public void setTermwiselimit(double value) {
         if ((value < 0.0) || (value > 1.0)) {
@@ -75,6 +79,9 @@ public class Matching implements Cloneable {
     public void setApproximateThreshold(double threshold) {
         approximateThreshold = threshold;
     }
+    public void setTargetHitsMaxAdjustmentFactor(double factor) {
+        targetHitsMaxAdjustmentFactor = factor;
+    }
 
     /** Internal operation - DO NOT USE */
     public void prepare(RankProperties rankProperties) {
@@ -97,6 +104,9 @@ public class Matching implements Cloneable {
         if (approximateThreshold != null) {
             rankProperties.put("vespa.matching.global_filter.lower_limit", String.valueOf(approximateThreshold));
         }
+        if (targetHitsMaxAdjustmentFactor != null) {
+            rankProperties.put("vespa.matching.nns.target_hits_max_adjustment_factor", String.valueOf(targetHitsMaxAdjustmentFactor));
+        }
     }
 
     @Override
@@ -119,12 +129,14 @@ public class Matching implements Cloneable {
                 Objects.equals(numSearchPartitions, matching.numSearchPartitions) &&
                 Objects.equals(minHitsPerThread, matching.minHitsPerThread) &&
                 Objects.equals(postFilterThreshold, matching.postFilterThreshold) &&
-                Objects.equals(approximateThreshold, matching.approximateThreshold);
+                Objects.equals(approximateThreshold, matching.approximateThreshold) &&
+                Objects.equals(targetHitsMaxAdjustmentFactor, matching.targetHitsMaxAdjustmentFactor);
     }
 
     @Override
     public int hashCode() {
-        return Objects.hash(termwiseLimit, numThreadsPerSearch, numSearchPartitions, minHitsPerThread, postFilterThreshold, approximateThreshold);
+        return Objects.hash(termwiseLimit, numThreadsPerSearch, numSearchPartitions, minHitsPerThread,
+                postFilterThreshold, approximateThreshold, targetHitsMaxAdjustmentFactor);
     }
 }
 
diff --git a/container-search/src/test/java/com/yahoo/search/query/MatchingTestCase.java b/container-search/src/test/java/com/yahoo/search/query/MatchingTestCase.java
index e3a1eb18a33..37d0e9e1072 100644
--- a/container-search/src/test/java/com/yahoo/search/query/MatchingTestCase.java
+++ b/container-search/src/test/java/com/yahoo/search/query/MatchingTestCase.java
@@ -20,6 +20,7 @@ public class MatchingTestCase {
         assertNull(query.getRanking().getMatching().getMinHitsPerThread());
         assertNull(query.getRanking().getMatching().getPostFilterThreshold());
         assertNull(query.getRanking().getMatching().getApproximateThreshold());
+        assertNull(query.getRanking().getMatching().getTargetHitsMaxAdjustmentFactor());
     }
 
     @Test
@@ -30,13 +31,15 @@ public class MatchingTestCase {
                 "&ranking.matching.numSearchPartitions=13" +
                 "&ranking.matching.minHitsPerThread=3" +
                 "&ranking.matching.postFilterThreshold=0.8" +
-                "&ranking.matching.approximateThreshold=0.3");
+                "&ranking.matching.approximateThreshold=0.3" +
+                "&ranking.matching.targetHitsMaxAdjustmentFactor=2.5");
         assertEquals(Double.valueOf(0.7), query.getRanking().getMatching().getTermwiseLimit());
         assertEquals(Integer.valueOf(17), query.getRanking().getMatching().getNumThreadsPerSearch());
         assertEquals(Integer.valueOf(13), query.getRanking().getMatching().getNumSearchPartitions());
         assertEquals(Integer.valueOf(3), query.getRanking().getMatching().getMinHitsPerThread());
         assertEquals(Double.valueOf(0.8), query.getRanking().getMatching().getPostFilterThreshold());
         assertEquals(Double.valueOf(0.3), query.getRanking().getMatching().getApproximateThreshold());
+        assertEquals(Double.valueOf(2.5), query.getRanking().getMatching().getTargetHitsMaxAdjustmentFactor());
 
         query.prepare();
         assertEquals("0.7", query.getRanking().getProperties().get("vespa.matching.termwise_limit").get(0));
@@ -45,6 +48,7 @@ public class MatchingTestCase {
         assertEquals("3", query.getRanking().getProperties().get("vespa.matching.minhitsperthread").get(0));
         assertEquals("0.8", query.getRanking().getProperties().get("vespa.matching.global_filter.upper_limit").get(0));
         assertEquals("0.3", query.getRanking().getProperties().get("vespa.matching.global_filter.lower_limit").get(0));
+        assertEquals("2.5", query.getRanking().getProperties().get("vespa.matching.nns.target_hits_max_adjustment_factor").get(0));
     }
 
     @Test
diff --git a/searchcore/src/tests/proton/matching/matching_test.cpp b/searchcore/src/tests/proton/matching/matching_test.cpp
index b59384f1493..6ef462f80c4 100644
--- a/searchcore/src/tests/proton/matching/matching_test.cpp
+++ b/searchcore/src/tests/proton/matching/matching_test.cpp
@@ -1135,12 +1135,12 @@ TEST("require that docsum matcher can extract matching elements from single attr
     EXPECT_EQUAL(list[1], 3u);
 }
 
-struct GlobalFilterParamsFixture {
+struct AttributeBlueprintParamsFixture {
    BlueprintFactory factory;
    search::fef::test::IndexEnvironment index_env;
    RankSetup rank_setup;
    Properties rank_properties;
-    GlobalFilterParamsFixture(double lower_limit, double upper_limit)
+   AttributeBlueprintParamsFixture(double lower_limit, double upper_limit, double target_hits_max_adjustment_factor)
        : factory(),
          index_env(),
          rank_setup(factory, index_env),
@@ -1148,32 +1148,37 @@ struct GlobalFilterParamsFixture {
    {
        rank_setup.set_global_filter_lower_limit(lower_limit);
        rank_setup.set_global_filter_upper_limit(upper_limit);
+       rank_setup.set_target_hits_max_adjustment_factor(target_hits_max_adjustment_factor);
    }
-   void set_query_properties(vespalib::stringref lower_limit, vespalib::stringref upper_limit) {
+   void set_query_properties(vespalib::stringref lower_limit, vespalib::stringref upper_limit,
+                             vespalib::stringref target_hits_max_adjustment_factor) {
        rank_properties.add(GlobalFilterLowerLimit::NAME, lower_limit);
        rank_properties.add(GlobalFilterUpperLimit::NAME, upper_limit);
+       rank_properties.add(TargetHitsMaxAdjustmentFactor::NAME, target_hits_max_adjustment_factor);
    }
    AttributeBlueprintParams extract(uint32_t active_docids = 9, uint32_t docid_limit = 10) const {
-       return MatchToolsFactory::extract_global_filter_params(rank_setup, rank_properties, active_docids, docid_limit);
+       return MatchToolsFactory::extract_attribute_blueprint_params(rank_setup, rank_properties, active_docids, docid_limit);
    }
 };
 
-TEST_F("global filter params are extracted from rank profile", GlobalFilterParamsFixture(0.2, 0.8))
+TEST_F("attribute blueprint params are extracted from rank profile", AttributeBlueprintParamsFixture(0.2, 0.8, 5.0))
 {
     auto params = f.extract();
     EXPECT_EQUAL(0.2, params.global_filter_lower_limit);
     EXPECT_EQUAL(0.8, params.global_filter_upper_limit);
+    EXPECT_EQUAL(5.0, params.target_hits_max_adjustment_factor);
 }
 
-TEST_F("global filter params are extracted from query", GlobalFilterParamsFixture(0.2, 0.8))
+TEST_F("attribute blueprint params are extracted from query", AttributeBlueprintParamsFixture(0.2, 0.8, 5.0))
 {
-    f.set_query_properties("0.15", "0.75");
+    f.set_query_properties("0.15", "0.75", "3.0");
     auto params = f.extract();
     EXPECT_EQUAL(0.15, params.global_filter_lower_limit);
     EXPECT_EQUAL(0.75, params.global_filter_upper_limit);
+    EXPECT_EQUAL(3.0, params.target_hits_max_adjustment_factor);
 }
 
-TEST_F("global filter params are scaled with active hit ratio", GlobalFilterParamsFixture(0.2, 0.8))
+TEST_F("global filter params are scaled with active hit ratio", AttributeBlueprintParamsFixture(0.2, 0.8, 5.0))
 {
     auto params = f.extract(5, 10);
     EXPECT_EQUAL(0.12, params.global_filter_lower_limit);
diff --git a/searchcore/src/vespa/searchcore/proton/matching/match_tools.cpp b/searchcore/src/vespa/searchcore/proton/matching/match_tools.cpp
index c7cbdc29689..a353d4816f6 100644
--- a/searchcore/src/vespa/searchcore/proton/matching/match_tools.cpp
+++ b/searchcore/src/vespa/searchcore/proton/matching/match_tools.cpp
@@ -176,11 +176,11 @@ MatchToolsFactory(QueryLimiter               & queryLimiter,
                   const search::IDocumentMetaStoreContext::IReadGuard::SP * metaStoreReadGuard,
                   bool                         is_search)
     : _queryLimiter(queryLimiter),
-      _global_filter_params(extract_global_filter_params(rankSetup, rankProperties, metaStore.getNumActiveLids(), searchContext.getDocIdLimit())),
+      _attribute_blueprint_params(extract_attribute_blueprint_params(rankSetup, rankProperties, metaStore.getNumActiveLids(), searchContext.getDocIdLimit())),
       _query(),
       _match_limiter(),
       _queryEnv(indexEnv, attributeContext, rankProperties, searchContext.getIndexes()),
-      _requestContext(doom, attributeContext, _queryEnv, _queryEnv.getObjectStore(), _global_filter_params, metaStoreReadGuard),
+      _requestContext(doom, attributeContext, _queryEnv, _queryEnv.getObjectStore(), _attribute_blueprint_params, metaStoreReadGuard),
       _mdl(),
       _rankSetup(rankSetup),
       _featureOverrides(featureOverrides),
@@ -203,8 +203,8 @@ MatchToolsFactory(QueryLimiter               & queryLimiter,
         _query.fetchPostings();
         if (is_search) {
             _query.handle_global_filter(searchContext.getDocIdLimit(),
-                                        _global_filter_params.global_filter_lower_limit,
-                                        _global_filter_params.global_filter_upper_limit,
+                                        _attribute_blueprint_params.global_filter_lower_limit,
+                                        _attribute_blueprint_params.global_filter_upper_limit,
                                         thread_bundle, trace);
         }
         _query.freeze();
@@ -324,18 +324,20 @@ MatchToolsFactory::get_feature_rename_map() const
 }
 
 AttributeBlueprintParams
-MatchToolsFactory::extract_global_filter_params(const RankSetup& rank_setup, const Properties& rank_properties,
-                                                uint32_t active_docids, uint32_t docid_limit)
+MatchToolsFactory::extract_attribute_blueprint_params(const RankSetup& rank_setup, const Properties& rank_properties,
+                                                      uint32_t active_docids, uint32_t docid_limit)
 {
     double lower_limit = GlobalFilterLowerLimit::lookup(rank_properties, rank_setup.get_global_filter_lower_limit());
     double upper_limit = GlobalFilterUpperLimit::lookup(rank_properties, rank_setup.get_global_filter_upper_limit());
+    double target_hits_max_adjustment_factor = TargetHitsMaxAdjustmentFactor::lookup(rank_properties, rank_setup.get_target_hits_max_adjustment_factor());
 
     // Note that we count the reserved docid 0 as active.
     // This ensures that when searchable-copies=1, the ratio is 1.0.
     double active_hit_ratio = std::min(active_docids + 1, docid_limit) / static_cast<double>(docid_limit);
 
     return {lower_limit * active_hit_ratio,
-            upper_limit * active_hit_ratio};
+            upper_limit * active_hit_ratio,
+            target_hits_max_adjustment_factor};
 }
 
 AttributeOperationTask::AttributeOperationTask(const RequestContext & requestContext,
diff --git a/searchcore/src/vespa/searchcore/proton/matching/match_tools.h b/searchcore/src/vespa/searchcore/proton/matching/match_tools.h
index db30ea8d2b2..681690d4c36 100644
--- a/searchcore/src/vespa/searchcore/proton/matching/match_tools.h
+++ b/searchcore/src/vespa/searchcore/proton/matching/match_tools.h
@@ -121,7 +121,7 @@ private:
     using IIndexEnvironment = search::fef::IIndexEnvironment;
     using IDiversifier = search::queryeval::IDiversifier;
     QueryLimiter                     & _queryLimiter;
-    AttributeBlueprintParams           _global_filter_params;
+    AttributeBlueprintParams           _attribute_blueprint_params;
     Query                              _query;
     MaybeMatchPhaseLimiter::UP         _match_limiter;
     std::unique_ptr<RangeQueryLocator> _rangeLocator;
@@ -177,15 +177,15 @@ public:
     const StringStringMap & get_feature_rename_map() const;
 
     /**
-     * Extracts global filter parameters from the rank-profile and query.
+     * Extracts attribute blueprint parameters from the rank-profile and query.
      *
-     * These parameters are expected to be in the range [0.0, 1.0], which matches the range of the estimated hit ratio of the query.
+     * The global filter parameters are expected to be in the range [0.0, 1.0], which matches the range of the estimated hit ratio of the query.
      * When searchable-copies > 1, we must scale the parameters to match the effective range of the estimated hit ratio.
      * This is done by multiplying with the active hit ratio (active docids / docid limit).
      */
     static AttributeBlueprintParams
-    extract_global_filter_params(const RankSetup& rank_setup, const Properties& rank_properties,
-                                 uint32_t active_docids, uint32_t docid_limit);
+    extract_attribute_blueprint_params(const RankSetup& rank_setup, const Properties& rank_properties,
+                                       uint32_t active_docids, uint32_t docid_limit);
 };
 
 }
diff --git a/searchlib/src/tests/attribute/tensorattribute/tensorattribute_test.cpp b/searchlib/src/tests/attribute/tensorattribute/tensorattribute_test.cpp
index 6ca7d298ee2..0475f8462fc 100644
--- a/searchlib/src/tests/attribute/tensorattribute/tensorattribute_test.cpp
+++ b/searchlib/src/tests/attribute/tensorattribute/tensorattribute_test.cpp
@@ -1320,15 +1320,16 @@ public:
         return *_query_tensor;
     }
 
-    std::unique_ptr<NearestNeighborBlueprint> make_blueprint(bool approximate = true, double global_filter_lower_limit = 0.05) {
+    std::unique_ptr<NearestNeighborBlueprint> make_blueprint(bool approximate = true,
+                                                             double global_filter_lower_limit = 0.05,
+                                                             double target_hits_max_adjustment_factor = 20.0) {
         search::queryeval::FieldSpec field("foo", 0, 0);
         auto bp = std::make_unique<NearestNeighborBlueprint>(
             field,
             std::make_unique<DistanceCalculator>(this->as_dense_tensor(),
                                                  create_query_tensor(vec_2d(17, 42))),
-            3, approximate, 5,
-            100100.25,
-            global_filter_lower_limit, 1.0, _no_doom.get_doom());
+            3, approximate, 5, 100100.25,
+            global_filter_lower_limit, 1.0, target_hits_max_adjustment_factor, _no_doom.get_doom());
         EXPECT_EQUAL(11u, bp->getState().estimate().estHits);
         EXPECT_EQUAL(100100.25 * 100100.25, bp->get_distance_threshold());
         return bp;
@@ -1362,6 +1363,19 @@ TEST_F("NN blueprint handles empty filter (post-filtering)", NearestNeighborBlue
     EXPECT_EQUAL(NNBA::INDEX_TOP_K, bp->get_algorithm());
 }
 
+TEST_F("NN blueprint adjustment of targetHits is bound (post-filtering)", NearestNeighborBlueprintFixture)
+{
+    auto bp = f.make_blueprint(true, 0.05, 3.5);
+    auto empty_filter = GlobalFilter::create();
+    bp->set_global_filter(*empty_filter, 0.2);
+    // targetHits is adjusted based on the estimated hit ratio of the query,
+    // but bound by target-hits-max-adjustment-factor
+    EXPECT_EQUAL(3u, bp->get_target_hits());
+    EXPECT_EQUAL(10u, bp->get_adjusted_target_hits());
+    EXPECT_EQUAL(10u, bp->getState().estimate().estHits);
+    EXPECT_EQUAL(NNBA::INDEX_TOP_K, bp->get_algorithm());
+}
+
 TEST_F("NN blueprint handles strong filter (pre-filtering)", NearestNeighborBlueprintFixture)
 {
     auto bp = f.make_blueprint();
diff --git a/searchlib/src/tests/ranksetup/ranksetup_test.cpp b/searchlib/src/tests/ranksetup/ranksetup_test.cpp
index 50d9d36f575..f708df0a862 100644
--- a/searchlib/src/tests/ranksetup/ranksetup_test.cpp
+++ b/searchlib/src/tests/ranksetup/ranksetup_test.cpp
@@ -533,6 +533,9 @@ void RankSetupTest::testRankSetup()
     env.getProperties().add(mutate::on_second_phase::Operation::NAME, "=7");
     env.getProperties().add(mutate::on_summary::Attribute::NAME, "c");
     env.getProperties().add(mutate::on_summary::Operation::NAME, "-=2");
+    env.getProperties().add(matching::GlobalFilterLowerLimit::NAME, "0.3");
+    env.getProperties().add(matching::GlobalFilterUpperLimit::NAME, "0.7");
+    env.getProperties().add(matching::TargetHitsMaxAdjustmentFactor::NAME, "5.0");
 
     RankSetup rs(_factory, env);
     EXPECT_FALSE(rs.has_match_features());
@@ -571,7 +574,9 @@ void RankSetupTest::testRankSetup()
     EXPECT_EQUAL(rs.getMutateOnSecondPhase()._operation, "=7");
     EXPECT_EQUAL(rs.getMutateOnSummary()._attribute, "c");
     EXPECT_EQUAL(rs.getMutateOnSummary()._operation, "-=2");
-
+    EXPECT_EQUAL(rs.get_global_filter_lower_limit(), 0.3);
+    EXPECT_EQUAL(rs.get_global_filter_upper_limit(), 0.7);
+    EXPECT_EQUAL(rs.get_target_hits_max_adjustment_factor(), 5.0);
 }
 
 bool
diff --git a/searchlib/src/vespa/searchlib/attribute/attribute_blueprint_factory.cpp b/searchlib/src/vespa/searchlib/attribute/attribute_blueprint_factory.cpp
index be631be6dca..453b7b321b9 100644
--- a/searchlib/src/vespa/searchlib/attribute/attribute_blueprint_factory.cpp
+++ b/searchlib/src/vespa/searchlib/attribute/attribute_blueprint_factory.cpp
@@ -842,14 +842,16 @@ public:
         }
         try {
             auto calc = tensor::DistanceCalculator::make_with_validation(_attr, *query_tensor);
+            const auto& params = getRequestContext().get_attribute_blueprint_params();
             setResult(std::make_unique<queryeval::NearestNeighborBlueprint>(_field,
                                                                             std::move(calc),
                                                                             n.get_target_num_hits(),
                                                                             n.get_allow_approximate(),
                                                                             n.get_explore_additional_hits(),
                                                                             n.get_distance_threshold(),
-                                                                            getRequestContext().get_attribute_blueprint_params().global_filter_lower_limit,
-                                                                            getRequestContext().get_attribute_blueprint_params().global_filter_upper_limit,
+                                                                            params.global_filter_lower_limit,
+                                                                            params.global_filter_upper_limit,
+                                                                            params.target_hits_max_adjustment_factor,
                                                                             getRequestContext().getDoom()));
         } catch (const vespalib::IllegalArgumentException& ex) {
             return fail_nearest_neighbor_term(n, ex.getMessage());
diff --git a/searchlib/src/vespa/searchlib/attribute/attribute_blueprint_params.h b/searchlib/src/vespa/searchlib/attribute/attribute_blueprint_params.h
index 39f58c5382e..64213235c23 100644
--- a/searchlib/src/vespa/searchlib/attribute/attribute_blueprint_params.h
+++ b/searchlib/src/vespa/searchlib/attribute/attribute_blueprint_params.h
@@ -13,17 +13,21 @@ struct AttributeBlueprintParams
 {
     double global_filter_lower_limit;
     double global_filter_upper_limit;
+    double target_hits_max_adjustment_factor;
 
     AttributeBlueprintParams(double global_filter_lower_limit_in,
-                             double global_filter_upper_limit_in)
+                             double global_filter_upper_limit_in,
+                             double target_hits_max_adjustment_factor_in)
         : global_filter_lower_limit(global_filter_lower_limit_in),
-          global_filter_upper_limit(global_filter_upper_limit_in)
+          global_filter_upper_limit(global_filter_upper_limit_in),
+          target_hits_max_adjustment_factor(target_hits_max_adjustment_factor_in)
     {
     }
 
     AttributeBlueprintParams()
         : AttributeBlueprintParams(fef::indexproperties::matching::GlobalFilterLowerLimit::DEFAULT_VALUE,
-                                   fef::indexproperties::matching::GlobalFilterUpperLimit::DEFAULT_VALUE)
+                                   fef::indexproperties::matching::GlobalFilterUpperLimit::DEFAULT_VALUE,
+                                   fef::indexproperties::matching::TargetHitsMaxAdjustmentFactor::DEFAULT_VALUE)
     {
     }
 };
diff --git a/searchlib/src/vespa/searchlib/fef/indexproperties.cpp b/searchlib/src/vespa/searchlib/fef/indexproperties.cpp
index 8be44ce0a0c..7871e66970e 100644
--- a/searchlib/src/vespa/searchlib/fef/indexproperties.cpp
+++ b/searchlib/src/vespa/searchlib/fef/indexproperties.cpp
@@ -422,6 +422,22 @@ GlobalFilterUpperLimit::lookup(const Properties &props, double defaultValue)
     return lookupDouble(props, NAME, defaultValue);
 }
 
+const vespalib::string TargetHitsMaxAdjustmentFactor::NAME("vespa.matching.nns.target_hits_max_adjustment_factor");
+
+const double TargetHitsMaxAdjustmentFactor::DEFAULT_VALUE(20.0);
+
+double
+TargetHitsMaxAdjustmentFactor::lookup(const Properties& props)
+{
+    return lookup(props, DEFAULT_VALUE);
+}
+
+double
+TargetHitsMaxAdjustmentFactor::lookup(const Properties& props, double defaultValue)
+{
+    return lookupDouble(props, NAME, defaultValue);
+}
+
 } // namespace matching
 
 namespace softtimeout {
diff --git a/searchlib/src/vespa/searchlib/fef/indexproperties.h b/searchlib/src/vespa/searchlib/fef/indexproperties.h
index f538e7bef2e..4f38a27d3fe 100644
--- a/searchlib/src/vespa/searchlib/fef/indexproperties.h
+++ b/searchlib/src/vespa/searchlib/fef/indexproperties.h
@@ -313,6 +313,21 @@ namespace matching {
         static double lookup(const Properties &props);
         static double lookup(const Properties &props, double defaultValue);
     };
+
+    /**
+     * Property to control the auto-adjustment of targetHits in a nearestNeighbor search using HNSW index with post-filtering.
+     *
+     * The targetHits is auto-adjusted in an effort to expose targetHits hits to first-phase ranking after post-filtering:
+     * adjustedTargetHits = min(targetHits / estimatedHitRatio, targetHits * targetHitsMaxAdjustmentFactor).
+     *
+     * This property ensures an upper bound of adjustedTargetHits, avoiding that the search in the HNSW index takes too long.
+     **/
+    struct TargetHitsMaxAdjustmentFactor {
+        static const vespalib::string NAME;
+        static const double DEFAULT_VALUE;
+        static double lookup(const Properties &props);
+        static double lookup(const Properties &props, double defaultValue);
+    };
 }
 
 namespace softtimeout {
diff --git a/searchlib/src/vespa/searchlib/fef/ranksetup.cpp b/searchlib/src/vespa/searchlib/fef/ranksetup.cpp
index 823e39199df..9d4e547feef 100644
--- a/searchlib/src/vespa/searchlib/fef/ranksetup.cpp
+++ b/searchlib/src/vespa/searchlib/fef/ranksetup.cpp
@@ -68,6 +68,7 @@ RankSetup::RankSetup(const BlueprintFactory &factory, const IIndexEnvironment &i
       _softTimeoutTailCost(0.1),
       _global_filter_lower_limit(0.0),
       _global_filter_upper_limit(1.0),
+      _target_hits_max_adjustment_factor(20.0),
       _mutateOnMatch(),
       _mutateOnFirstPhase(),
       _mutateOnSecondPhase(),
@@ -121,6 +122,7 @@ RankSetup::configure()
     setSoftTimeoutTailCost(softtimeout::TailCost::lookup(_indexEnv.getProperties()));
     set_global_filter_lower_limit(matching::GlobalFilterLowerLimit::lookup(_indexEnv.getProperties()));
     set_global_filter_upper_limit(matching::GlobalFilterUpperLimit::lookup(_indexEnv.getProperties()));
+    set_target_hits_max_adjustment_factor(matching::TargetHitsMaxAdjustmentFactor::lookup(_indexEnv.getProperties()));
     _mutateOnMatch._attribute = mutate::on_match::Attribute::lookup(_indexEnv.getProperties());
     _mutateOnMatch._operation = mutate::on_match::Operation::lookup(_indexEnv.getProperties());
     _mutateOnFirstPhase._attribute = mutate::on_first_phase::Attribute::lookup(_indexEnv.getProperties());
diff --git a/searchlib/src/vespa/searchlib/fef/ranksetup.h b/searchlib/src/vespa/searchlib/fef/ranksetup.h
index 832b86d042a..72432c2ed8a 100644
--- a/searchlib/src/vespa/searchlib/fef/ranksetup.h
+++ b/searchlib/src/vespa/searchlib/fef/ranksetup.h
@@ -76,6 +76,7 @@ private:
     double                   _softTimeoutTailCost;
     double                   _global_filter_lower_limit;
     double                   _global_filter_upper_limit;
+    double                   _target_hits_max_adjustment_factor;
     MutateOperation          _mutateOnMatch;
     MutateOperation          _mutateOnFirstPhase;
     MutateOperation          _mutateOnSecondPhase;
@@ -393,6 +394,8 @@ public:
     double get_global_filter_lower_limit() const { return _global_filter_lower_limit; }
     void set_global_filter_upper_limit(double v) { _global_filter_upper_limit = v; }
     double get_global_filter_upper_limit() const { return _global_filter_upper_limit; }
+    void set_target_hits_max_adjustment_factor(double v) { _target_hits_max_adjustment_factor = v; }
+    double get_target_hits_max_adjustment_factor() const { return _target_hits_max_adjustment_factor; }
 
     /**
      * This method may be used to indicate that certain features
diff --git a/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.cpp b/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.cpp
index 87ddb8b6edc..32b5148f706 100644
--- a/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.cpp
+++ b/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.cpp
@@ -43,6 +43,7 @@ NearestNeighborBlueprint::NearestNeighborBlueprint(const queryeval::FieldSpec& f
                                                    double distance_threshold,
                                                    double global_filter_lower_limit,
                                                    double global_filter_upper_limit,
+                                                   double target_hits_max_adjustment_factor,
                                                    const vespalib::Doom& doom)
     : ComplexLeafBlueprint(field),
       _distance_calc(std::move(distance_calc)),
@@ -55,6 +56,7 @@ NearestNeighborBlueprint::NearestNeighborBlueprint(const queryeval::FieldSpec& f
       _distance_threshold(std::numeric_limits<double>::max()),
       _global_filter_lower_limit(global_filter_lower_limit),
       _global_filter_upper_limit(global_filter_upper_limit),
+      _target_hits_max_adjustment_factor(target_hits_max_adjustment_factor),
       _distance_heap(target_hits),
       _found_hits(),
       _algorithm(Algorithm::EXACT),
@@ -95,8 +97,10 @@ NearestNeighborBlueprint::set_global_filter(const GlobalFilter &global_filter, d
         } else { // post-filtering case
             // The goal is to expose 'targetHits' hits to first-phase ranking.
             // We try to achieve this by adjusting targetHits based on the estimated hit ratio of the query before post-filtering.
+            // However, this is bound by 'target-hits-max-adjustment-factor' to limit the cost of searching the HNSW index.
             if (estimated_hit_ratio > 0.0) {
-                _adjusted_target_hits = static_cast<double>(_target_hits) / estimated_hit_ratio;
+                _adjusted_target_hits = std::min(static_cast<double>(_target_hits) / estimated_hit_ratio,
+                                                 static_cast<double>(_target_hits) * _target_hits_max_adjustment_factor);
             }
         }
         if (_algorithm != Algorithm::EXACT_FALLBACK) {
diff --git a/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.h b/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.h
index f88cdd5adb1..174f0b23125 100644
--- a/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.h
+++ b/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.h
@@ -38,6 +38,7 @@ private:
     double _distance_threshold;
     double _global_filter_lower_limit;
     double _global_filter_upper_limit;
+    double _target_hits_max_adjustment_factor;
     mutable NearestNeighborDistanceHeap _distance_heap;
     std::vector<search::tensor::NearestNeighborIndex::Neighbor> _found_hits;
     Algorithm _algorithm;
@@ -55,6 +56,7 @@ public:
                              double distance_threshold,
                              double global_filter_lower_limit,
                              double global_filter_upper_limit,
+                             double target_hits_max_adjustment_factor,
                              const vespalib::Doom& doom);
     NearestNeighborBlueprint(const NearestNeighborBlueprint&) = delete;
     NearestNeighborBlueprint& operator=(const NearestNeighborBlueprint&) = delete;