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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.

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

Types of term-level queries

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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.
wildcard query: Returns documents that contain terms matching a wildcard pattern.

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