Fix NPE in flat_bbq scorer when all vectors are missing #129548
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
benwtrent
added
>bug
:Search Relevance/Vectors
elasticsearchmachine
added
the
Team:Search Relevance
|
Pinging @elastic/es-search-relevance (Team:Search Relevance) |
|
Hi @benwtrent, I've created a changelog YAML for you. |
benwtrent
added
the
auto-backport
benwtrent
added
auto-merge-without-approval
💔 Backport failed
You can use sqren/backport to manually backport by running |
benwtrent
added a commit
to benwtrent/elasticsearch
that referenced
this pull request
Jun 18, 2025
It is possible to get all the way down to the knn format reader and there be no vectors in the index. This execution path is possible if utilizing nested queries (which bypasses the higher level checks in `KnnFloatVectorQuery#approximateSearch`). bbq_flat should check for the existence of vectors before attempting to create the scorer. (cherry picked from commit 80667d0)
This was referenced Jun 18, 2025
💚 All backports created successfully
Questions ?Please refer to the Backport tool documentation |
benwtrent
added a commit
to benwtrent/elasticsearch
that referenced
this pull request
Jun 18, 2025
It is possible to get all the way down to the knn format reader and there be no vectors in the index. This execution path is possible if utilizing nested queries (which bypasses the higher level checks in `KnnFloatVectorQuery#approximateSearch`). bbq_flat should check for the existence of vectors before attempting to create the scorer. (cherry picked from commit 80667d0)
elasticsearchmachine
pushed a commit
that referenced
this pull request
Jun 18, 2025
… (#129623) * Fix NPE in flat_bbq scorer when all vectors are missing (#129548) It is possible to get all the way down to the knn format reader and there be no vectors in the index. This execution path is possible if utilizing nested queries (which bypasses the higher level checks in `KnnFloatVectorQuery#approximateSearch`). bbq_flat should check for the existence of vectors before attempting to create the scorer. (cherry picked from commit 80667d0) * fixing comp
elasticsearchmachine
pushed a commit
that referenced
this pull request
Jun 18, 2025
…) (#129624) * Fix NPE in flat_bbq scorer when all vectors are missing (#129548) It is possible to get all the way down to the knn format reader and there be no vectors in the index. This execution path is possible if utilizing nested queries (which bypasses the higher level checks in `KnnFloatVectorQuery#approximateSearch`). bbq_flat should check for the existence of vectors before attempting to create the scorer. (cherry picked from commit 80667d0) * fixing comp
elasticsearchmachine
pushed a commit
that referenced
this pull request
Jun 18, 2025
…) (#129625) * Fix NPE in flat_bbq scorer when all vectors are missing (#129548) It is possible to get all the way down to the knn format reader and there be no vectors in the index. This execution path is possible if utilizing nested queries (which bypasses the higher level checks in `KnnFloatVectorQuery#approximateSearch`). bbq_flat should check for the existence of vectors before attempting to create the scorer. (cherry picked from commit 80667d0) * fixing compilation
kderusso
pushed a commit
to kderusso/elasticsearch
that referenced
this pull request
Jun 23, 2025
It is possible to get all the way down to the knn format reader and there be no vectors in the index. This execution path is possible if utilizing nested queries (which bypasses the higher level checks in `KnnFloatVectorQuery#approximateSearch`). bbq_flat should check for the existence of vectors before attempting to create the scorer.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
It is possible to get all the way down to the knn format reader and there be no vectors in the index.
This execution path is possible if utilizing nested queries (which bypasses the higher level checks in
KnnFloatVectorQuery#approximateSearch).bbq_flat should check for the existence of vectors before attempting to create the scorer.