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Search

OpenSearch provides several features for customizing your search use cases and improving search relevance. In OpenSearch, you can:

Use SQL and Piped Processing Language (PPL) as alternatives to query domain-specific language (DSL) for searching data.
Run resource-intensive queries asynchronously with asynchronous search.
Search for k-nearest neighbors with k-NN search.
Abstract OpenSearch queries into search templates.
Integrate machine learning (ML) language models into your search workloads with neural search.
Compare search results to tune search relevance.
Use a dataset that is fixed in time to paginate results with Point in Time.
Paginate and sort search results, highlight search terms, and use the autocomplete and did-you-mean functionality.
Rewrite queries with Querqy.
Process search queries and search results with search pipelines.