elasticsearch/docs/reference/query-languages/term-level-queries.md
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Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
Co-authored-by: Liam Thompson <leemthompo@gmail.com>
Co-authored-by: Martijn Laarman <Mpdreamz@gmail.com>
Co-authored-by: István Zoltán Szabó <szabosteve@gmail.com>
2025-02-27 17:56:14 +01:00

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https://www.elastic.co/guide/en/elasticsearch/reference/current/term-level-queries.html

Term-level queries [term-level-queries]

You can use term-level queries to find documents based on precise values in structured data. Examples of structured data include date ranges, IP addresses, prices, or product IDs.

Unlike full-text queries, term-level queries do not analyze search terms. Instead, term-level queries match the exact terms stored in a field.

::::{note} Term-level queries still normalize search terms for keyword fields with the normalizer property. For more details, see normalizer.

::::

Types of term-level queries [term-level-query-types]

exists query
Returns documents that contain any indexed value for a field.
fuzzy query
Returns documents that contain terms similar to the search term. {{es}} measures similarity, or fuzziness, using a Levenshtein edit distance.
ids query
Returns documents based on their document IDs.
prefix query
Returns documents that contain a specific prefix in a provided field.
range query
Returns documents that contain terms within a provided range.
regexp query
Returns documents that contain terms matching a regular expression.
term query
Returns documents that contain an exact term in a provided field.
terms query
Returns documents that contain one or more exact terms in a provided field.
terms_set query
Returns documents that contain a minimum number of exact terms in a provided field. You can define the minimum number of matching terms using a field or script.
wildcard query
Returns documents that contain terms matching a wildcard pattern.