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* Add search pipeline documentation Signed-off-by: Fanit Kolchina <[email protected]> * Add search pipeline documentation Signed-off-by: Fanit Kolchina <[email protected]> * Add search pipeline documentation Signed-off-by: Fanit Kolchina <[email protected]> * Add experimental label Signed-off-by: Fanit Kolchina <[email protected]> * Update script processor Signed-off-by: Fanit Kolchina <[email protected]> * Implemented tech review comments Signed-off-by: Fanit Kolchina <[email protected]> * Add wildcard and pipeline path parameter Signed-off-by: Fanit Kolchina <[email protected]> * Reworded get pipeline responses Signed-off-by: Fanit Kolchina <[email protected]> * Add we do not recommend to use the feature in prod Signed-off-by: Fanit Kolchina <[email protected]> * Apply suggestions from code review Co-authored-by: Melissa Vagi <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> * Add header to table Signed-off-by: Fanit Kolchina <[email protected]> * Apply suggestions from code review Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> * Implemented tech review and editorial comments Signed-off-by: Fanit Kolchina <[email protected]> --------- Signed-off-by: Fanit Kolchina <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> Co-authored-by: Melissa Vagi <[email protected]> Co-authored-by: Nathan Bower <[email protected]>
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layout, title, nav_order, has_children, has_toc, nav_exclude
| layout | title | nav_order | has_children | has_toc | nav_exclude |
|---|---|---|---|---|---|
| default | Search | 1 | false | false | true |
Search
OpenSearch provides several features for customizing your search use cases and improving search relevance. In OpenSearch, you can:
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Use SQL and Piped Processing Language (PPL) as alternatives to query domain-specific language (DSL) to search data.
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Run resource-intensive queries asynchronously with asynchronous search.
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Search for k-nearest neighbors with k-NN search.
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Abstract OpenSearch queries into search templates.
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Integrate machine learning (ML) language models into your search workloads with neural search.
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Compare search results to tune search relevance.
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Use a dataset that is fixed in time to paginate results with Point in Time.
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Paginate and sort search results, highlight search terms, and use the autocomplete and did-you-mean functionality.
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Rewrite queries with Querqy.
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Process search queries and search results with search pipelines.