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- [role="xpack"]
- [testenv="basic"]
- [[sql-like-rlike-operators]]
- === LIKE and RLIKE Operators
- `LIKE` and `RLIKE` operators are commonly used to filter data based on string patterns. They usually act on a field placed on the left-hand side of
- the operator, but can also act on a constant (literal) expression. The right-hand side of the operator represents the pattern.
- Both can be used in the `WHERE` clause of the `SELECT` statement, but `LIKE` can also be used in other places, such as defining an
- <<sql-index-patterns, index pattern>> or across various <<sql-commands, SHOW commands>>.
- This section covers only the `SELECT ... WHERE ...` usage.
- NOTE: One significant difference between `LIKE`/`RLIKE` and the <<sql-functions-search, full-text search predicates>> is that the former
- act on <<sql-multi-field, exact fields>> while the latter also work on <<text, analyzed>> fields. If the field used with `LIKE`/`RLIKE` doesn't
- have an exact not-normalized sub-field (of <<keyword, keyword>> type) {es-sql} will not be able to run the query. If the field is either exact
- or has an exact sub-field, it will use it as is, or it will automatically use the exact sub-field even if it wasn't explicitly specified in the statement.
- [[sql-like-operator]]
- ==== `LIKE`
- .Synopsis:
- [source, sql]
- --------------------------------------------------
- expression <1>
- LIKE constant_exp <2>
- --------------------------------------------------
- <1> typically a field, or a constant expression
- <2> pattern
- .Description:
- The SQL `LIKE` operator is used to compare a value to similar values using wildcard operators. There are two wildcards used in conjunction
- with the `LIKE` operator:
- * The percent sign (%)
- * The underscore (_)
- The percent sign represents zero, one or multiple characters. The underscore represents a single number or character. These symbols can be
- used in combinations.
- [source, sql]
- ----
- include-tagged::{sql-specs}/docs/docs.csv-spec[simpleLike]
- ----
- There is, also, the possibility of using an escape character if one needs to match the wildcard characters themselves. This can be done
- by using the `ESCAPE [escape_character]` statement after the `LIKE ...` operator:
- SELECT name, author FROM library WHERE name LIKE 'Dune/%' ESCAPE '/';
- In the example above `/` is defined as an escape character which needs to be placed before the `%` or `_` characters if one needs to
- match those characters in the pattern specifically. By default, there is no escape character defined.
- IMPORTANT: Even though `LIKE` is a valid option when searching or filtering in {es-sql}, full-text search predicates
- `MATCH` and `QUERY` are <<sql-like-prefer-full-text, faster and much more powerful and are the preferred alternative>>.
- [[sql-rlike-operator]]
- ==== `RLIKE`
- .Synopsis:
- [source, sql]
- --------------------------------------------------
- expression <1>
- RLIKE constant_exp <2>
- --------------------------------------------------
- <1> typically a field, or a constant expression
- <2> pattern
- .Description:
- This operator is similar to `LIKE`, but the user is not limited to search for a string based on a fixed pattern with the percent sign (`%`)
- and underscore (`_`); the pattern in this case is a regular expression which allows the construction of more flexible patterns.
- For more details about the regular expressions syntax, https://docs.oracle.com/en/java/javase/11/docs/api/java.base/java/util/regex/Pattern.html[Java's Pattern class javadoc]
- is a good starting point.
- [source, sql]
- ----
- include-tagged::{sql-specs}/docs/docs.csv-spec[simpleRLike]
- ----
- IMPORTANT: Even though `RLIKE` is a valid option when searching or filtering in {es-sql}, full-text search predicates
- `MATCH` and `QUERY` are <<sql-like-prefer-full-text, faster and much more powerful and are the preferred alternative>>.
- [[sql-like-prefer-full-text]]
- ==== Prefer full-text search predicates
- When using `LIKE`/`RLIKE`, do consider using <<sql-functions-search, full-text search predicates>> which are faster, much more powerful
- and offer the option of sorting by relevancy (results can be returned based on how well they matched).
- For example:
- [cols="<m,<m"]
- |===
- ^s|LIKE/RLIKE ^s|QUERY/MATCH
- |`foo LIKE 'bar'` |`MATCH(foo, 'bar')`
- |`foo LIKE 'bar' AND tar LIKE 'goo'` |`MATCH('foo^2, tar^5', 'bar goo', 'operator=and')`
- |`foo LIKE 'barr'` |`QUERY('foo: bar~')`
- |`foo LIKE 'bar' AND tar LIKE 'goo'` |`QUERY('foo: bar AND tar: goo')`
- |`foo RLIKE 'ba.*'` |`MATCH(foo, 'ba', 'fuzziness=AUTO:1,5')`
- |`foo RLIKE 'b.{1}r'` |`MATCH(foo, 'br', 'fuzziness=1')`
- |===
|