Movatterモバイル変換


[0]ホーム

URL:


Loading
  1. Elastic Docs/
  2. Reference/
  3. Query languages/
  4. QueryDSL

Term-level queries

You can useterm-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.

Unlikefull-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 forkeyword fields with thenormalizer property. For more details, seenormalizer.

exists query
Returns documents that contain any indexed value for a field.
fuzzy query
Returns documents that contain terms similar to the search term. Elasticsearch measures similarity, or fuzziness, using aLevenshtein edit distance.
ids query
Returns documents based on theirdocument 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 aregular 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.

[8]ページ先頭

©2009-2026 Movatter.jp