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Term-level queries
editTerm-level queries
editYou 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
edit-
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.