feat: native Elasticsearch vector search support

[joaopamaral]

Summary

Adds native Elasticsearch 9.x vector search support, mirroring the existing OpenSearch implementation. OpenMetadata deployments backed by Elasticsearch 9.x can now use the same semantic/vector search features as OpenSearch deployments.

Architecture: ES vs OpenSearch Vector Search

                    ┌─────────────────────────────────────────────────────────────┐
                    │                   VectorIndexService (interface)             │
                    │  search() · updateEntityEmbedding() · getExistingFingerprint │
                    │  generateEmbeddingFields()                                   │
                    └───────────────┬───────────────────────┬───────────────────┘
                                    │                       │
               ┌────────────────────▼──────┐   ┌───────────▼──────────────────┐
               │  OpenSearchVectorService  │   │  ElasticSearchVectorService   │
               │  (existing, unchanged)    │   │  (new)                        │
               ├───────────────────────────┤   ├──────────────────────────────┤
               │ Transport: generic client  │   │ Transport: Rest5Client        │
               │ Query: query.knn (nested)  │   │ Query: top-level knn object   │
               │ Index field: knn_vector    │   │ Index field: dense_vector     │
               │                           │   │                               │
               │ Hybrid pipeline: ✅        │   │ Hybrid pipeline: ✗ (ES        │
               │  ensureHybridSearchPipeline│   │  doesn't support RRF pipeline │
               │  (OpenSearch RRF)          │   │  via search pipeline API)     │
               └───────────────────────────┘   └──────────────────────────────┘
                          │                                  │
               ┌──────────▼──────────┐           ┌──────────▼──────────┐
               │   OpenSearch index  │           │ Elasticsearch index  │
               │                     │           │                      │
               │ embedding:          │           │ embedding:           │
               │   type: knn_vector  │           │   type: dense_vector │
               │   dimension: N      │           │   dims: N            │
               │   method:           │           │   similarity: cosine │
               │     name: hnsw      │           │   (ES 9.x BBQ-HNSW)  │
               │     engine: lucene  │           │                      │
               │     space: cosine   │           │                      │
               └─────────────────────┘           └──────────────────────┘

Query format difference

OpenSearch (query.knn — nested under "query")   Elasticsearch (top-level knn)
─────────────────────────────────────────────   ─────────────────────────────
{                                               {
  "query": {                                      "knn": {
    "knn": {                                        "field": "embedding",
      "embedding": {                                "query_vector": [...],
        "vector": [...],                            "k": 10,
        "k": 10,                                    "num_candidates": 100,
        "filter": { ... }                           "filter": { ... }
      }                                           }
    }                                           }
  }
}

Ingestion flow

Entity created/updated
        │
        ▼
VectorEmbeddingHandler (lifecycle event)
        │
        ▼
VectorDocBuilder.buildEmbeddingFields()
  · textToLLMContext (concatenated text)
  · fingerprint (SHA-256, change detection)
  · embedding (float[] from EmbeddingClient)
  · parentId, chunkIndex, chunkCount
        │
        ├──── OpenSearch ──▶ OpenSearchVectorService.partialUpdateEntity()
        │                      POST /{index}/_update/{id}  (generic client)
        │
        └──── Elasticsearch ▶ ElasticSearchVectorService.partialUpdateEntity()
                               POST /{index}/_update/{id}  (Rest5Client)

Changes

New

• ElasticSearchVectorService: ES implementation of VectorIndexService. Uses Rest5Client for all HTTP calls (same approach as the rest of the ES client layer). Mirrors OpenSearchVectorService for pagination, fingerprint deduplication, and embedding lifecycle.
• vector_search_index_es_native.json (en/jp/ru/zh): ES-native index mappings using dense_vector / dims / cosine similarity (ES 9.x format).
• SemanticSearchQueryBuilder (ES package): mirrors the OpenSearch equivalent.
• VectorSearchQueryBuilder.buildNativeESQuery(): emits the ES 9.x top-level knn format with configurable num_candidates.

Modified

• ElasticSearchIndexManager.extractMappingsJson(): extracts the mappings sub-object before putMapping — ES rejects the full index JSON (with settings/aliases) at the mappings endpoint.
• EsUtils.enrichIndexMappingForElasticsearch(): injects dense_vector field into ES index mappings when vector search is enabled.
• SearchRepository: wires ElasticSearchVectorService for the ELASTICSEARCH search type; applies enrichIndexMappingForElasticsearch to index templates (OpenSearch path unchanged).
• ElasticSearchBulkSink: calls vectorIndexService.updateEntityEmbedding() on write, same as OpenSearchBulkSink.
• VectorSearchQueryBuilder: reformatVectorIndexWithDimension() handles both "dims" (ES) and "dimension" (OpenSearch).

Bug fixes (post-review)

• appendKnnQuery closing braces: }}}} → }}} — the extra brace produced malformed JSON, causing OpenSearch to return 400 on every KNN request (silently yielding empty results).
• executeGenericRequest HTTP status check: now throws on 4xx/5xx instead of silently returning {}.
• extractRestClient type guard: replaces unchecked cast with instanceof pattern match; throws IllegalArgumentException with the actual transport class name on mismatch.
• knnNumCandidatesMultiplier: wired from naturalLanguageSearch.knnNumCandidatesMultiplier config; defaults to 2×.
• getFingerprint endpoint: gated to admin users.
• Index template enrichment: createOrUpdateIndexTemplates() and createOrUpdateIndexTemplate() now call enrichIndexMappingForElasticsearch() so templates include dense_vector when vector search is enabled.

Review-feedback fixes (commit 9854029a)

• SystemRepository.getEmbeddingsValidation(): removed the ES short-circuit. Elasticsearch now flows through the same checks (embedding generation + hybrid pipeline) as OpenSearch instead of always failing with the legacy "not supported" message.
• EsUtils.addDenseVectorSettings(): detects _meta.embedding_dimension drift vs. the active embedding client and emits a WARN log, mirroring OsUtils.addKnnVectorSettings. Helps surface stale indexes after a model switch (e.g. DJL 384 → OpenAI 1536).
• ElasticSearchBulkSink.isVectorEmbeddingEnabledForEntity: also gates on searchRepository.getIndexMapping(entityType) != null to skip entities whose mapping isn't loaded.
• ElasticSearchBulkSink.fetchExistingFingerprints: takes a ReindexContext and routes to the staged index when one exists. Without this the fingerprint dedup reads the canonical (old) index during a staged reindex and re-processes everything it was supposed to skip.
• New unit tests for each of the above (in EsUtilsTest, ElasticSearchBulkSinkBehaviorTest, SystemRepositoryEmbeddingsValidationTest).

Test plan

• mvn test -pl openmetadata-service -Dtest=VectorSearchQueryBuilderTest,ElasticSearchIndexManagerTest,ElasticSearchVectorServiceTest,SearchRepositoryBehaviorTest,EsUtilsTest,ElasticSearchBulkSinkBehaviorTest,SystemRepositoryEmbeddingsValidationTest
• mvn test -pl openmetadata-integration-tests -Dtest=VectorEmbeddingIntegrationIT (uses Testcontainers OpenSearch 3.4.0)
• Local end-to-end on ES 9.3.0 + DJL all-MiniLM-L6-v2: top-1 accuracy 3/3 across distinct semantic queries (revenue from sales → customer_purchases 0.76; login authentication → user_logins 0.71; temperature humidity → weather_data 0.69). Index has dense_vector{dims:384, similarity:cosine, BBQ-HNSW}. See docs/elasticsearch-semantic-search-local-test.md.
• No regression on OpenSearch 3.4.0: same test re-run with SEARCH_TYPE=opensearch. OpenSearchVectorService initializes, hybrid-rrf pipeline registered, knn_vector mapping created, semantic queries return identical scores to ES (same embedding model → deterministic cosine ranking).
• End-to-end re-verified after the review-feedback fixes on both ES 9.3.0 and OpenSearch 3.4.0 — identical scores to the original run, no regression.

References

• Elasticsearch k-nearest neighbor (kNN) search

🤖 Generated with Claude Code

---

Summary by Gitar

• Vector search configuration:
  • Refactored VectorSearchQueryBuilder to clean up clamping logic for num_candidates to ensure robustness against integer overflow.
• ElasticSearch integration:
  • Removed redundant interface constants in ElasticSearchVectorService to streamline the service implementation.

_{This will update automatically on new commits.}

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[joaopamaral]

Initial results look good, but I've run a test only with ES 9.x and version 1.12.4 (not the one from main). I also need to double-check if OpenSearch is affected by this change. Also need to review some AI-resolved conflicts from version 1.12.4 with main.

[harshach]

Thanks @joaopamaral this is great!!. Can you make it ready for review? and also address comments here #27111 (comment)

[joaopamaral]

Sure @harshach! I'll work on the bot review first before making it ready for review! 👍

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[github-actions]

Hi there 👋 Thanks for your contribution!

The OpenMetadata team will review the PR shortly! Once it has been labeled as safe to test, the CI workflows
will start executing and we'll be able to make sure everything is working as expected.

Let us know if you need any help!

[joaopamaral]

Hi @harshach, ’ve addressed the bot review, but I still need to re-review the code after rebasing/merging with main and rerun the tests against a real server. So far, I’ve tested this PR with version 1.12.4 and ES 9.3.1. I still need to validate that everything continues to work correctly with OpenSearch and ES 8.x.

I won’t be able to run tests for the next couple of days, but feel free to proceed with any testing on your side in the meantime.

[Copilot]

Pull request overview

This PR adds native Elasticsearch (8.x/9.x) vector search support to OpenMetadata, aiming to provide semantic/vector search capabilities on Elasticsearch deployments comparable to the existing OpenSearch implementation.

Changes:

• Added a new ElasticSearchVectorService plus wiring in SearchRepository / ElasticSearchBulkSink to initialize and use it when Elasticsearch is the configured backend.
• Introduced ES-native vector index mapping templates (vector_search_index_es_native.json) and extended query-building to emit Elasticsearch’s top-level knn query format.
• Added/updated tests around the ES-native query format and Elasticsearch vector service behavior.

Reviewed changes

Copilot reviewed 20 out of 20 changed files in this pull request and generated 10 comments.

Show a summary per file

File	Description
openmetadata-spec/src/main/resources/json/schema/search/searchRequest.json	Adds semanticSearch flag to the search request schema.
openmetadata-spec/src/main/resources/elasticsearch/en/vector_search_index_es_native.json	New ES-native vector index template (en).
openmetadata-spec/src/main/resources/elasticsearch/jp/vector_search_index_es_native.json	New ES-native vector index template (jp).
openmetadata-spec/src/main/resources/elasticsearch/ru/vector_search_index_es_native.json	New ES-native vector index template (ru).
openmetadata-spec/src/main/resources/elasticsearch/zh/vector_search_index_es_native.json	New ES-native vector index template (zh).
openmetadata-service/src/main/java/org/openmetadata/service/search/vector/VectorSearchQueryBuilder.java	Adds buildNativeESQuery and refactors filter emission for vector search queries.
openmetadata-service/src/test/java/org/openmetadata/service/search/vector/VectorSearchQueryBuilderTest.java	Adds coverage for ES-native top-level knn query structure and filter behavior.
openmetadata-service/src/main/java/org/openmetadata/service/search/vector/VectorIndexService.java	Extends vector service interface and adds an alias helper.
openmetadata-service/src/main/java/org/openmetadata/service/search/vector/OpenSearchVectorService.java	Adjusts to use the new interface default alias method and annotates overrides.
openmetadata-service/src/main/java/org/openmetadata/service/search/vector/ElasticSearchVectorService.java	New Elasticsearch vector service implementation using Rest5Client for generic requests.
openmetadata-service/src/test/java/org/openmetadata/service/search/vector/ElasticSearchVectorServiceTest.java	New tests for ES vector service result parsing, grouping, and dimension patching.
openmetadata-service/src/main/java/org/openmetadata/service/search/SearchRepository.java	Initializes ES vector service when Elasticsearch backend is configured; mapping selection tweaks for ES-native template.
openmetadata-service/src/main/java/org/openmetadata/service/search/RecreateWithEmbeddings.java	Attempts to include a vector “entity” key in recreate flow when vector search is enabled.
openmetadata-service/src/main/java/org/openmetadata/service/search/elasticsearch/SemanticSearchQueryBuilder.java	New builder for semantic/hybrid query composition on Elasticsearch.
openmetadata-service/src/main/java/org/openmetadata/service/search/elasticsearch/ElasticSearchIndexManager.java	Extracts mappings sub-object before calling putMapping.
openmetadata-service/src/test/java/org/openmetadata/service/search/elasticsearch/ElasticSearchIndexManagerTest.java	Adds a test asserting updateIndex handles full index JSON by extracting mappings.
openmetadata-service/src/main/java/org/openmetadata/service/resources/search/VectorSearchResource.java	Switches to repository-provided VectorIndexService and adds a fingerprint endpoint.
openmetadata-service/src/main/java/org/openmetadata/service/apps/bundles/searchIndex/ElasticSearchBulkSink.java	Adds async vector-embedding task execution + migration path for ES indexing jobs.
openmetadata-service/src/test/java/org/openmetadata/service/apps/bundles/searchIndex/ElasticSearchBulkSinkSimpleTest.java	Adds minimal coverage for vector-embedding helpers on the ES sink.
openmetadata-mcp/src/main/java/org/openmetadata/mcp/tools/SemanticSearchTool.java	Uses repository VectorIndexService rather than OpenSearch-only implementation.

[joaopamaral]

Also need to review all after this refactor #26000 😢

[harshach]

@joaopamaral thanks for your work on this, can you check the co-pilot comments and address the merge conflict here please

[github-actions]

The Java checkstyle failed.

Please run mvn spotless:apply in the root of your repository and commit the changes to this PR.
You can also use pre-commit to automate the Java code formatting.

You can install the pre-commit hooks with make install_test precommit_install.

[github-actions]

⚠️ TypeScript Types Need Update

The generated TypeScript types are out of sync with the JSON schema changes.

Since this is a pull request from a forked repository, the types cannot be automatically committed.
Please generate and commit the types manually:

cd openmetadata-ui/src/main/resources/ui
./json2ts-generate-all.sh -l true
git add src/generated/
git commit -m "Update generated TypeScript types"
git push

After pushing the changes, this check will pass automatically.

[Copilot]

Pull request overview

Copilot reviewed 22 out of 24 changed files in this pull request and generated 1 comment.

Comments suppressed due to low confidence (1)

openmetadata-service/src/main/java/org/openmetadata/service/search/SearchRepository.java:393

• createOrUpdateIndexTemplates() catches all exceptions from mapping enrichment (including IllegalStateException from EsUtils.enrichIndexMappingForElasticsearch on embedding dimension drift) and only logs e.getMessage() at WARN. This effectively downgrades a critical misconfiguration to a soft failure and also drops the stack trace, making the root cause harder to diagnose. Consider either (a) logging the full exception (pass e to the logger) and/or (b) rethrowing/propagating dimension-mismatch failures so startup/reindex clearly fails and operators are forced to reindex as intended.

  public void createOrUpdateIndexTemplates() {
    LOG.info("Creating/updating index templates for all entities...");
    int success = 0;
    int failed = 0;
    for (Map.Entry<String, IndexMapping> entry : entityIndexMap.entrySet()) {
      try {
        IndexMapping indexMapping = entry.getValue();
        String indexName = indexMapping.getIndexName(clusterAlias);
        String templateName = "om_" + indexName;
        String indexPattern = indexName + "*";
        String mappingContent = enrichForElasticsearch(readIndexMapping(indexMapping));
        if (mappingContent != null) {
          searchClient.createOrUpdateIndexTemplate(templateName, indexPattern, mappingContent);
          success++;
        } else {
          failed++;
          LOG.warn("No mapping content found for entity type: {}", entry.getKey());
        }
      } catch (Exception e) {
        failed++;
        LOG.warn("Failed to create index template for {}: {}", entry.getKey(), e.getMessage());
      }

[github-actions]

Jest test Coverage

UI tests summary

Lines	Statements	Branches	Functions
	62.45% (62922/100755)	42.77% (33911/79285)	45.77% (10035/21924)

[Copilot]

Pull request overview

Copilot reviewed 22 out of 24 changed files in this pull request and generated no new comments.

[joaopamaral]

Copilot reviewed 22 out of 24 changed files in this pull request and generated no new comments.

@lautel I think Copilot is happy now 😄

[github-actions]

Jest test Coverage

UI tests summary

Lines	Statements	Branches	Functions
	62.45% (62922/100755)	42.77% (33911/79285)	45.77% (10035/21924)

[github-actions]

Jest test Coverage

UI tests summary

Lines	Statements	Branches	Functions
	62.45% (62922/100755)	42.77% (33911/79285)	45.77% (10035/21924)

[lautel]

There's just one clean up to do and the PR should be good to get it in 🚀 Please check my comment to remove the dead code in ElasticSearchVectorService. Also please solve the merge conflict, and don't forget to run mvn spotless:apply before committing to apply the right formatting! Thanks!

[Copilot]

Pull request overview

Copilot reviewed 22 out of 24 changed files in this pull request and generated 3 comments.

[github-actions]

Jest test Coverage

UI tests summary

Lines	Statements	Branches	Functions
	62.45% (62922/100755)	42.77% (33911/79285)	45.77% (10035/21924)

[github-actions]

The Java checkstyle failed.

Please run mvn spotless:apply in the root of your repository and commit the changes to this PR.
You can also use pre-commit to automate the Java code formatting.

You can install the pre-commit hooks with make install_test precommit_install.

[Copilot]

Pull request overview

Copilot reviewed 22 out of 24 changed files in this pull request and generated no new comments.

[github-actions]

Jest test Coverage

UI tests summary

Lines	Statements	Branches	Functions
	62.42% (62939/100817)	42.75% (33918/79324)	45.75% (10035/21934)

[github-actions]

The Java checkstyle failed.

Please run mvn spotless:apply in the root of your repository and commit the changes to this PR.
You can also use pre-commit to automate the Java code formatting.

You can install the pre-commit hooks with make install_test precommit_install.

[gitar-bot]

Code Review 👍 Approved with suggestions 6 resolved / 7 findings

Native Elasticsearch vector search integration implemented with robust handling for index mappings and client transport safety. Address the minor fanout logic discrepancy where null targets currently return only staged indices.

💡 Edge Case: getWriteFanoutTargets(null) returns only staged indices

📄 openmetadata-service/src/main/java/org/openmetadata/service/search/SearchRepository.java:630-632

When aliasOrIndex is null, getWriteFanoutTargets returns new ArrayList<>(activeStagedIndices.values()) — i.e. only the staged indices without any base/alias target. If a caller passes null expecting an empty or no-op result, it will instead fan writes to all staged indices. This is unlikely to be hit in practice since callers resolve index names from mappings, but the null-handling semantics are surprising compared to getWriteIndexName(null) which returns null.

Suggested fix

if (aliasOrIndex == null) {
  return Collections.emptyList();
}

✅ 6 resolved

✅ Bug: Test calls build() with 4 args but method requires 6 — won't compile

📄 openmetadata-service/src/test/java/org/openmetadata/service/search/vector/VectorSearchQueryBuilderTest.java:864 📄 openmetadata-service/src/main/java/org/openmetadata/service/search/vector/VectorSearchQueryBuilder.java:19-25
The test testNativeESQueryAndOpenSearchQueryProduceSameFilters at line 864 calls VectorSearchQueryBuilder.build(vector, 10, 100, filters) with 4 arguments, but the build() method signature requires 6 parameters: (float[] vector, int size, int from, int k, Map<String, List<String>> filters, double threshold). This will fail to compile. The intent appears to be comparing OpenSearch and ES native queries with the same filters.

✅ Edge Case: loadIndexMapping dimension replacement is brittle — exact string match

📄 openmetadata-service/src/main/java/org/openmetadata/service/search/vector/ElasticSearchVectorService.java:523-527 📄 openmetadata-service/src/main/java/org/openmetadata/service/search/SearchRepository.java:3060-3068
In ElasticSearchVectorService.loadIndexMapping(), the dimension placeholder is replaced via exact string matching: template.replace(""dims": 512", ""dims": " + dimension). This requires the JSON template to have exactly one space after the colon. If the template is reformatted (e.g., minified, or extra spaces), the replacement silently fails. The code does have a post-check that throws if no replacement happened, but the same brittleness exists in SearchRepository.reformatVectorIndexWithDimension() fallback (lines 3062-3068) which does multiple .replace() calls for both with-space and without-space variants — showing awareness of the problem but an incomplete fix.

✅ Edge Case: init() assigns instance before registerVectorEmbeddingHandler completes

📄 openmetadata-service/src/main/java/org/openmetadata/service/search/vector/ElasticSearchVectorService.java:65-79
In ElasticSearchVectorService.init() (line 70), instance is assigned the new service object, and then instance.registerVectorEmbeddingHandler() is called on line 71. Since getInstance() is not synchronized, a concurrent caller could observe the instance in a partially-initialized state (before the handler is registered). The volatile keyword ensures the reference is visible but doesn't guarantee that registerVectorEmbeddingHandler() has completed.

This mirrors the existing OpenSearch pattern, but the ES version is new code where it can be fixed.

✅ Bug: ES search pagination is broken vs OpenSearch implementation

📄 openmetadata-service/src/main/java/org/openmetadata/service/search/vector/ElasticSearchVectorService.java:95-109 📄 openmetadata-service/src/main/java/org/openmetadata/service/search/vector/OpenSearchVectorService.java:196-210
The ElasticSearchVectorService.search() passes from directly to the ES kNN query, which skips raw hits (chunks). However, the API contract expects from to skip parent entities (grouped results). The OpenSearch implementation correctly handles this: it fetches from + size + 1 parents via a loop, then skips from parents in application code.

With the current ES implementation, requesting from=5, size=10 skips 5 raw chunks (not 5 parents), leading to incorrect pagination results. Additionally, the ES version uses the 2-arg VectorSearchResponse constructor, so totalHits and hasMore are always null — callers lose pagination metadata.

✅ Quality: Unsafe downcast defeats purpose of VectorIndexService interface

📄 openmetadata-service/src/main/java/org/openmetadata/service/apps/bundles/searchIndex/ElasticSearchBulkSink.java:778
ElasticSearchBulkSink casts vectorService to (ElasticSearchVectorService) to call copyExistingVectorDocuments(). This couples the sink back to the concrete class, undermining the new interface abstraction. If vectorService is ever a different implementation, this throws ClassCastException at runtime.

...and 1 more resolved from earlier reviews

🤖 Prompt for agents

Code Review: Native Elasticsearch vector search integration implemented with robust handling for index mappings and client transport safety. Address the minor fanout logic discrepancy where null targets currently return only staged indices.

1. 💡 Edge Case: getWriteFanoutTargets(null) returns only staged indices
   Files: openmetadata-service/src/main/java/org/openmetadata/service/search/SearchRepository.java:630-632

   When `aliasOrIndex` is `null`, `getWriteFanoutTargets` returns `new ArrayList<>(activeStagedIndices.values())` — i.e. only the staged indices without any base/alias target. If a caller passes `null` expecting an empty or no-op result, it will instead fan writes to all staged indices. This is unlikely to be hit in practice since callers resolve index names from mappings, but the null-handling semantics are surprising compared to `getWriteIndexName(null)` which returns `null`.

   Suggested fix:
   if (aliasOrIndex == null) {
     return Collections.emptyList();
   }

Options

Display: compact → Showing less information.

Comment with these commands to change:

Compact

gitar display:verbose

_{Was this helpful? React with 👍 / 👎 | Gitar}

[Copilot]

Pull request overview

Copilot reviewed 22 out of 24 changed files in this pull request and generated no new comments.

[github-actions]

Jest test Coverage

UI tests summary

Lines	Statements	Branches	Functions
	62.42% (62939/100817)	42.75% (33918/79324)	45.75% (10035/21934)

[sonarqubecloud]

Quality Gate passed for 'open-metadata-ui'

Issues
1067 New issues
0 Accepted issues

Measures
17 Security Hotspots
0.0% Coverage on New Code
3.8% Duplication on New Code

See analysis details on SonarQube Cloud

[sonarqubecloud]

Quality Gate passed for 'open-metadata-ingestion'

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud

[joaopamaral]

hey @lautel, the failing tests in CI don't seem related to this PR