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Merge branch '9.1' into backport/9.1/pr-130090
2 parents 437e43f + cf1c7ec commit cf2000a

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.buildkite/scripts/run-pr-upgrade-tests.sh

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# Identify the merge base of the current commit (branch) and the base branch of the pull request.
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# PR upgrade tests are run from the merge base to the current commit.
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BASE_COMMIT=$(git merge-base $BUILDKITE_PULL_REQUEST_BASE_BRANCH $BUILDKITE_COMMIT)
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git fetch origin $BUILDKITE_PULL_REQUEST_BASE_BRANCH
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BASE_COMMIT=$(git merge-base origin/$BUILDKITE_PULL_REQUEST_BASE_BRANCH $BUILDKITE_COMMIT)
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VERSION=$(sed -n 's/^elasticsearch[[:space:]]*=[[:space:]]*\(.*\)/\1/p' build-tools-internal/version.properties)
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docs/reference/query-languages/query-dsl/query-dsl-knn-query.md

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Note that nested `knn` only supports `score_mode=max`.
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## Knn query on a semantic_text field [knn-query-with-semantic-text]
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Elasticsearch supports knn queries over a [
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`semantic_text` field](/reference/elasticsearch/mapping-reference/semantic-text.md).
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Here is an example using the `query_vector_builder`:
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```json
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{
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"query": {
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"knn": {
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"field": "inference_field",
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"k": 10,
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"num_candidates": 100,
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"query_vector_builder": {
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"text_embedding": {
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"model_text": "test"
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}
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}
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}
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}
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}
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```
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Note that for `semantic_text` fields, the `model_id` does not have to be
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provided as it can be inferred from the `semantic_text` field mapping.
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Knn search using query vectors over `semantic_text` fields is also supported,
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with no change to the API.
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## Knn query with aggregations [knn-query-aggregations]
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`knn` query calculates aggregations on top `k` documents from each shard. Thus, the final results from aggregations contain `k * number_of_shards` documents. This is different from the [top level knn section](docs-content://solutions/search/vector/knn.md) where aggregations are calculated on the global top `k` nearest documents.

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