Term-level queries | Elasticsearch Guide [7.7]

原文地址: https://www.elastic.co/guide/en/elasticsearch/reference/7.7/term-level-queries.html, 原文档版权归 www.elastic.co 所有

IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.

» »

« Pinned Query Exists query »

Term-level queriesedit

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.

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

Types of term-level queriesedit

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 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.
type query: Returns documents of the specified type.
wildcard query: Returns documents that contain terms matching a wildcard pattern.

« Pinned Query Exists query »