163 lines
5.9 KiB
Plaintext
163 lines
5.9 KiB
Plaintext
[role="xpack"]
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[testenv="basic"]
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[[sql-functions-search]]
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=== Full-Text Search Functions
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Search functions should be used when performing full-text search, namely
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when the `MATCH` or `QUERY` predicates are being used.
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Outside a, so-called, search context, these functions will return default values
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such as `0` or `NULL`.
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[[sql-functions-search-match]]
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==== `MATCH`
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.Synopsis:
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[source, sql]
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--------------------------------------------------
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MATCH(
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field_exp, <1>
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constant_exp <2>
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[, options]) <3>
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--------------------------------------------------
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*Input*:
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<1> field(s) to match
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<2> matching text
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<3> additional parameters; optional
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.Description:
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A full-text search option, in the form of a predicate, available in {es-sql} that gives the user control over powerful <<query-dsl-match-query,match>>
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and <<query-dsl-multi-match-query,multi_match>> {es} queries.
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The first parameter is the field or fields to match against. In case it receives one value only, {es-sql} will use a `match` query to perform the search:
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[source, sql]
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----
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include-tagged::{sql-specs}/docs/docs.csv-spec[simpleMatch]
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----
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However, it can also receive a list of fields and their corresponding optional `boost` value. In this case, {es-sql} will use a
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`multi_match` query to match the documents:
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[source, sql]
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----
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include-tagged::{sql-specs}/docs/docs.csv-spec[multiFieldsMatch]
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----
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NOTE: The `multi_match` query in {es} has the option of <<query-dsl-multi-match-query,per-field boosting>> that gives preferential weight
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(in terms of scoring) to fields being searched in, using the `^` character. In the example above, the `name` field has a greater weight in
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the final score than the `author` field when searching for `frank dune` text in both of them.
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Both options above can be used in combination with the optional third parameter of the `MATCH()` predicate, where one can specify
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additional configuration parameters (separated by semicolon `;`) for either `match` or `multi_match` queries. For example:
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[source, sql]
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----
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include-tagged::{sql-specs}/docs/docs.csv-spec[optionalParamsForMatch]
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----
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In the more advanced example above, the `cutoff_frequency` parameter allows specifying an absolute or relative document frequency where
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high frequency terms are moved into an optional subquery and are only scored if one of the low frequency (below the cutoff) terms in the
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case of an `or` operator or all of the low frequency terms in the case of an `and` operator match. More about this you can find in the
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<<query-dsl-match-query-cutoff>> page.
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NOTE: The allowed optional parameters for a single-field `MATCH()` variant (for the `match` {es} query) are: `analyzer`, `auto_generate_synonyms_phrase_query`,
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`cutoff_frequency`, `lenient`, `fuzziness`, `fuzzy_transpositions`, `fuzzy_rewrite`, `minimum_should_match`, `operator`,
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`max_expansions`, `prefix_length`.
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NOTE: The allowed optional parameters for a multi-field `MATCH()` variant (for the `multi_match` {es} query) are: `analyzer`, `auto_generate_synonyms_phrase_query`,
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`cutoff_frequency`, `lenient`, `fuzziness`, `fuzzy_transpositions`, `fuzzy_rewrite`, `minimum_should_match`, `operator`,
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`max_expansions`, `prefix_length`, `slop`, `tie_breaker`, `type`.
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[[sql-functions-search-query]]
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==== `QUERY`
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.Synopsis:
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[source, sql]
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--------------------------------------------------
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QUERY(
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constant_exp <1>
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[, options]) <2>
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--------------------------------------------------
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*Input*:
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<1> query text
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<2> additional parameters; optional
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.Description:
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Just like `MATCH`, `QUERY` is a full-text search predicate that gives the user control over the <<query-dsl-query-string-query,query_string>> query in {es}.
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The first parameter is basically the input that will be passed as is to the `query_string` query, which means that anything that `query_string`
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accepts in its `query` field can be used here as well:
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[source, sql]
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----
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include-tagged::{sql-specs}/docs/docs.csv-spec[simpleQueryQuery]
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----
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A more advanced example, showing more of the features that `query_string` supports, of course possible with {es-sql}:
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[source, sql]
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----
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include-tagged::{sql-specs}/docs/docs.csv-spec[advancedQueryQuery]
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----
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The query above uses the `_exists_` query to select documents that have values in the `author` field, a range query for `page_count` and
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regex and fuzziness queries for the `name` field.
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If one needs to customize various configuration options that `query_string` exposes, this can be done using the second _optional_ parameter.
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Multiple settings can be specified separated by a semicolon `;`:
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[source, sql]
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----
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include-tagged::{sql-specs}/docs/docs.csv-spec[optionalParameterQuery]
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----
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NOTE: The allowed optional parameters for `QUERY()` are: `allow_leading_wildcard`, `analyze_wildcard`, `analyzer`,
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`auto_generate_synonyms_phrase_query`, `default_field`, `default_operator`, `enable_position_increments`,
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`escape`, `fuzziness`, `fuzzy_max_expansions`, `fuzzy_prefix_length`, `fuzzy_rewrite`, `fuzzy_transpositions`,
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`lenient`, `max_determinized_states`, `minimum_should_match`, `phrase_slop`, `rewrite`, `quote_analyzer`,
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`quote_field_suffix`, `tie_breaker`, `time_zone`, `type`.
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[[sql-functions-search-score]]
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==== `SCORE`
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.Synopsis:
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[source, sql]
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--------------------------------------------------
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SCORE()
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--------------------------------------------------
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*Input*: _none_
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*Output*: `double` numeric value
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.Description:
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Returns the {defguide}/relevance-intro.html[relevance] of a given input to the executed query.
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The higher score, the more relevant the data.
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NOTE: When doing multiple text queries in the `WHERE` clause then, their scores will be
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combined using the same rules as {es}'s
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<<query-dsl-bool-query,bool query>>.
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Typically `SCORE` is used for ordering the results of a query based on their relevance:
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[source, sql]
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----
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include-tagged::{sql-specs}/docs/docs.csv-spec[orderByScore]
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----
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However, it is perfectly fine to return the score without sorting by it:
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[source, sql]
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----
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include-tagged::{sql-specs}/docs/docs.csv-spec[scoreWithMatch]
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----
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