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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) for searching 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.