223 lines
6.6 KiB
Plaintext
223 lines
6.6 KiB
Plaintext
[[query-dsl-match-query]]
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=== Match Query
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A family of `match` queries that accept text/numerics/dates, analyzes
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it, and constructs a query out of it. For example:
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[source,js]
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--------------------------------------------------
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{
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"match" : {
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"message" : "this is a test"
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}
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}
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--------------------------------------------------
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Note, `message` is the name of a field, you can substitute the name of
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any field (including `_all`) instead.
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[float]
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==== Types of Match Queries
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[float]
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===== boolean
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The default `match` query is of type `boolean`. It means that the text
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provided is analyzed and the analysis process constructs a boolean query
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from the provided text. The `operator` flag can be set to `or` or `and`
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to control the boolean clauses (defaults to `or`). The minimum number of
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should clauses to match can be set using the
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<<query-dsl-minimum-should-match,`minimum_should_match`>>
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parameter.
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The `analyzer` can be set to control which analyzer will perform the
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analysis process on the text. It default to the field explicit mapping
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definition, or the default search analyzer.
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`fuzziness` can be set to a value (depending on the relevant type, for
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string types it should be a value between `0.0` and `1.0`) to constructs
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fuzzy queries for each term analyzed. The `prefix_length` and
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`max_expansions` can be set in this case to control the fuzzy process.
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If the fuzzy option is set the query will use `constant_score_rewrite`
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as its <<query-dsl-multi-term-rewrite,rewrite
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method>> the `rewrite` parameter allows to control how the query will get
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rewritten.
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Here is an example when providing additional parameters (note the slight
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change in structure, `message` is the field name):
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[source,js]
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--------------------------------------------------
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{
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"match" : {
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"message" : {
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"query" : "this is a test",
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"operator" : "and"
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}
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}
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}
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--------------------------------------------------
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zero_terms_query
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If the analyzer used removes all tokens in a query like a `stop` filter
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does, the default behavior is to match no documents at all. In order to
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change that the `zero_terms_query` option can be used, which accepts
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`none` (default) and `all` which corresponds to a `match_all` query.
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[source,js]
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--------------------------------------------------
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{
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"match" : {
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"message" : {
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"query" : "to be or not to be",
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"operator" : "and",
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"zero_terms_query": "all"
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}
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}
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}
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--------------------------------------------------
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cutoff_frequency
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Since `0.90.0` match query supports a `cutoff_frequency` that allows
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specifying an absolute or relative document frequency where high
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frequent terms are moved into an optional subquery and are only scored
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if one of the low frequent (below the cutoff) terms in the case of an
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`or` operator or all of the low frequent terms in the case of an `and`
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operator match.
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This query allows handling `stopwords` dynamically at runtime, is domain
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independent and doesn't require on a stopword file. It prevent scoring /
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iterating high frequent terms and only takes the terms into account if a
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more significant / lower frequent terms match a document. Yet, if all of
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the query terms are above the given `cutoff_frequency` the query is
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automatically transformed into a pure conjunction (`and`) query to
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ensure fast execution.
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The `cutoff_frequency` can either be relative to the number of documents
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in the index if in the range `[0..1)` or absolute if greater or equal to
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`1.0`.
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Here is an example showing a query composed of stopwords exclusivly:
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[source,js]
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--------------------------------------------------
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{
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"match" : {
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"message" : {
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"query" : "to be or not to be",
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"cutoff_frequency" : 0.001
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}
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}
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}
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--------------------------------------------------
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[float]
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===== phrase
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The `match_phrase` query analyzes the text and creates a `phrase` query
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out of the analyzed text. For example:
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[source,js]
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--------------------------------------------------
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{
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"match_phrase" : {
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"message" : "this is a test"
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}
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}
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--------------------------------------------------
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Since `match_phrase` is only a `type` of a `match` query, it can also be
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used in the following manner:
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[source,js]
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--------------------------------------------------
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{
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"match" : {
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"message" : {
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"query" : "this is a test",
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"type" : "phrase"
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}
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}
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}
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--------------------------------------------------
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A phrase query maintains order of the terms up to a configurable `slop`
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(which defaults to 0).
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The `analyzer` can be set to control which analyzer will perform the
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analysis process on the text. It default to the field explicit mapping
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definition, or the default search analyzer, for example:
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[source,js]
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--------------------------------------------------
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{
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"match_phrase" : {
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"message" : {
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"query" : "this is a test",
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"analyzer" : "my_analyzer"
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}
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}
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}
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--------------------------------------------------
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[float]
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===== match_phrase_prefix
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The `match_phrase_prefix` is the same as `match_phrase`, except that it
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allows for prefix matches on the last term in the text. For example:
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[source,js]
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--------------------------------------------------
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{
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"match_phrase_prefix" : {
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"message" : "this is a test"
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}
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}
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--------------------------------------------------
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Or:
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[source,js]
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--------------------------------------------------
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{
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"match" : {
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"message" : {
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"query" : "this is a test",
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"type" : "phrase_prefix"
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}
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}
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}
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--------------------------------------------------
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It accepts the same parameters as the phrase type. In addition, it also
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accepts a `max_expansions` parameter that can control to how many
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prefixes the last term will be expanded. It is highly recommended to set
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it to an acceptable value to control the execution time of the query.
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For example:
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[source,js]
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--------------------------------------------------
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{
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"match_phrase_prefix" : {
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"message" : {
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"query" : "this is a test",
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"max_expansions" : 10
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}
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}
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}
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--------------------------------------------------
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[float]
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==== Comparison to query_string / field
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The match family of queries does not go through a "query parsing"
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process. It does not support field name prefixes, wildcard characters,
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or other "advance" features. For this reason, chances of it failing are
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very small / non existent, and it provides an excellent behavior when it
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comes to just analyze and run that text as a query behavior (which is
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usually what a text search box does). Also, the `phrase_prefix` type can
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provide a great "as you type" behavior to automatically load search
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results.
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