Skip to content

Update VectorNestedIT to include more kNN search scenarios #131776

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jul 24, 2025
Merged

Update VectorNestedIT to include more kNN search scenarios #131776

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
88 changes: 88 additions & 0 deletions server/src/internalClusterTest/java/org/elasticsearch/search/nested/VectorNestedIT.java
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,8 +17,11 @@
import org.elasticsearch.test.ESIntegTestCase;

import java.util.List;
import java.util.Map;

import static org.elasticsearch.test.hamcrest.ElasticsearchAssertions.assertAcked;
import static org.elasticsearch.test.hamcrest.ElasticsearchAssertions.assertHitCount;
import static org.elasticsearch.test.hamcrest.ElasticsearchAssertions.assertNoFailuresAndResponse;
import static org.elasticsearch.test.hamcrest.ElasticsearchAssertions.assertResponse;
import static org.elasticsearch.xcontent.XContentFactory.jsonBuilder;
import static org.hamcrest.Matchers.equalTo;
Expand Down Expand Up @@ -75,4 +78,89 @@ public void testSimpleNested() throws Exception {
);
}

public void testNestedKNnnSearch() {
testNestedWithTwoSegments(false);
}

public void testNestedKNnnSearchWithMultipleSegments() {
testNestedWithTwoSegments(true);
}

private void testNestedWithTwoSegments(boolean flush) {
assertAcked(prepareCreate("test").setMapping("""
{
"properties": {
"name": {
"type": "keyword"
},
"nested": {
"type": "nested",
"properties": {
"paragraph_id": {
"type": "keyword"
},
"vector": {
"type": "dense_vector",
"dims": 5,
"similarity": "l2_norm",
"index_options": {
"type": "hnsw"
}
}
}
}
}
}
""").setSettings(Settings.builder().put(indexSettings()).put("index.number_of_shards", 1)));
ensureGreen();

prepareIndex("test").setId("1")
.setSource(
"name",
"dog",
"nested",
new Object[] {
Map.of("paragraph_id", 0, "vector", new float[] { 230.0f, 300.33f, -34.8988f, 15.555f, -200.0f }),
Map.of("paragraph_id", 1, "vector", new float[] { 240.0f, 300f, -3f, 1f, -20f }) }
)
.get();

prepareIndex("test").setId("2")
.setSource(
"name",
"cat",
"nested",
new Object[] {
Map.of("paragraph_id", 0, "vector", new float[] { -0.5f, 100.0f, -13f, 14.8f, -156.0f }),
Map.of("paragraph_id", 1, "vector", new float[] { 0f, 100.0f, 0f, 14.8f, -156.0f }),
Map.of("paragraph_id", 2, "vector", new float[] { 0f, 1.0f, 0f, 1.8f, -15.0f }) }
)
.get();

if (flush) {
refresh("test");
}

prepareIndex("test").setId("3")
.setSource(
"name",
"rat",
"nested",
new Object[] { Map.of("paragraph_id", 0, "vector", new float[] { 0.5f, 111.3f, -13.0f, 14.8f, -156.0f }) }
)
.get();

waitForRelocation(ClusterHealthStatus.GREEN);
refresh();

var knn = new KnnSearchBuilder("nested.vector", new float[] { -0.5f, 90.0f, -10f, 14.8f, -156.0f }, 2, 3, null, null);
var request = prepareSearch("test").addFetchField("name").setKnnSearch(List.of(knn));
assertNoFailuresAndResponse(request, response -> {
assertHitCount(response, 2);
assertEquals("2", response.getHits().getHits()[0].getId());
assertEquals("cat", response.getHits().getHits()[0].field("name").getValue());
assertEquals("3", response.getHits().getHits()[1].getId());
assertEquals("rat", response.getHits().getHits()[1].field("name").getValue());
});
}
}