IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Term level queries
editTerm level queries
editWhile the full text queries will analyze the query
string before executing, the term-level queries operate on the exact terms
that are stored in the inverted index, and will normalize terms before executing
only for keyword fields with normalizer property.
These queries are usually used for structured data like numbers, dates, and enums, rather than full text fields. Alternatively, they allow you to craft low-level queries, foregoing the analysis process.
The queries in this group are:
-
termquery - Find documents which contain the exact term specified in the field specified.
-
termsquery - Find documents which contain any of the exact terms specified in the field specified.
-
terms_setquery - Find documents which match with one or more of the specified terms. The number of terms that must match depend on the specified minimum should match field or script.
-
rangequery - Find documents where the field specified contains values (dates, numbers, or strings) in the range specified.
-
existsquery - Find documents where the field specified contains any non-null value.
-
prefixquery - Find documents where the field specified contains terms which begin with the exact prefix specified.
-
wildcardquery -
Find documents where the field specified contains terms which match the
pattern specified, where the pattern supports single character wildcards
(
?) and multi-character wildcards (*) -
regexpquery - Find documents where the field specified contains terms which match the regular expression specified.
-
fuzzyquery - Find documents where the field specified contains terms which are fuzzily similar to the specified term. Fuzziness is measured as a Levenshtein edit distance of 1 or 2.
-
typequery - Find documents of the specified type.
-
idsquery - Find documents with the specified type and IDs.