[Backport 2.x] Add support for scored named queries (#11626) #12427
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Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. This is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query. --------- Signed-off-by: Dharin Shah <[email protected]> Signed-off-by: Dharin Shah <[email protected]> Co-authored-by: Dharin Shah <[email protected]> (cherry picked from commit 52b27f4) Signed-off-by: Andrew Ross <[email protected]>
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Compatibility status:Checks if related components are compatible with change 56d080a Incompatible componentsSkipped componentsCompatible componentsCompatible components: [https://github.com/opensearch-project/asynchronous-search.git, https://github.com/opensearch-project/performance-analyzer-rca.git, https://github.com/opensearch-project/cross-cluster-replication.git, https://github.com/opensearch-project/job-scheduler.git, https://github.com/opensearch-project/reporting.git, https://github.com/opensearch-project/security.git, https://github.com/opensearch-project/common-utils.git, https://github.com/opensearch-project/geospatial.git, https://github.com/opensearch-project/index-management.git, https://github.com/opensearch-project/k-nn.git, https://github.com/opensearch-project/anomaly-detection.git, https://github.com/opensearch-project/custom-codecs.git, https://github.com/opensearch-project/observability.git, https://github.com/opensearch-project/flow-framework.git, https://github.com/opensearch-project/performance-analyzer.git, https://github.com/opensearch-project/alerting.git, https://github.com/opensearch-project/ml-commons.git, https://github.com/opensearch-project/neural-search.git, https://github.com/opensearch-project/security-analytics.git, https://github.com/opensearch-project/notifications.git, https://github.com/opensearch-project/sql.git] |
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❌ Gradle check result for ccbd26b: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
Ugh...some version guards need to be updated. This also means the guards on main will have to be changed as soon as this PR is committed otherwise bwc tests will break. |
Signed-off-by: Andrew Ross <[email protected]>
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❌ Gradle check result for 0aae97b: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
rest-api-spec/src/main/resources/rest-api-spec/test/search/350_matched_queries.yml
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Thanks @andrross ! |
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❌ Gradle check result for 346583f: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
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❌ Gradle check result for 5cc2675: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
Co-authored-by: Andriy Redko <[email protected]> Signed-off-by: Andrew Ross <[email protected]>
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❌ Gradle check result for 56d080a: null Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
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This check actually succeeded, but the GHA poller failed on one of its requests to Jenkins: https://build.ci.opensearch.org/job/gradle-check/34086/ |
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❕ Gradle check result for 56d080a: UNSTABLE
Please review all flaky tests that succeeded after retry and create an issue if one does not already exist to track the flaky failure. |
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@andrross my apologies, could you please bring this change to main? thank you
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Sorry i couldn't pick this up, thanks for handling it @andrross |
Opensearch already support labelling the queries, that returns as a list in the returned results, of which query it matched. However one of the use case while doing hybrid search with query text and dense vector is to determine individual scores for each query type. This is very useful in further analysis and building offline model to generate better weights for ranking score. Hence adding this feature that sends the client to add the score for each matched query.
(cherry picked from commit 52b27f4)
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