[[query-dsl-match-query]] === Match Query A family of `match` queries that accepts text/numerics/dates, analyzes them, and constructs a query. For example: [source,js] -------------------------------------------------- { "match" : { "message" : "this is a test" } } -------------------------------------------------- Note, `message` is the name of a field, you can substitute the name of any field (including `_all`) instead. There are three types of `match` query: `boolean`, `phrase`, and `phrase_prefix`: [[query-dsl-match-query-boolean]] ==== boolean The default `match` query is of type `boolean`. It means that the text provided is analyzed and the analysis process constructs a boolean query from the provided text. The `operator` flag can be set to `or` or `and` to control the boolean clauses (defaults to `or`). The minimum number of optional `should` clauses to match can be set using the <> parameter. The `analyzer` can be set to control which analyzer will perform the analysis process on the text. It defaults to the field explicit mapping definition, or the default search analyzer. The `lenient` parameter can be set to `true` to ignore exceptions caused by data-type mismatches, such as trying to query a numeric field with a text query string. Defaults to `false`. [[query-dsl-match-query-fuzziness]] ===== Fuzziness `fuzziness` allows _fuzzy matching_ based on the type of field being queried. See <> for allowed settings. The `prefix_length` and `max_expansions` can be set in this case to control the fuzzy process. If the fuzzy option is set the query will use `top_terms_blended_freqs_${max_expansions}` as its <> the `fuzzy_rewrite` parameter allows to control how the query will get rewritten. Fuzzy transpositions (`ab` -> `ba`) are allowed by default but can be disabled by setting `fuzzy_transpositions` to `false`. Here is an example when providing additional parameters (note the slight change in structure, `message` is the field name): [source,js] -------------------------------------------------- { "match" : { "message" : { "query" : "this is a test", "operator" : "and" } } } -------------------------------------------------- [[query-dsl-match-query-zero]] ===== Zero terms query If the analyzer used removes all tokens in a query like a `stop` filter does, the default behavior is to match no documents at all. In order to change that the `zero_terms_query` option can be used, which accepts `none` (default) and `all` which corresponds to a `match_all` query. [source,js] -------------------------------------------------- { "match" : { "message" : { "query" : "to be or not to be", "operator" : "and", "zero_terms_query": "all" } } } -------------------------------------------------- [[query-dsl-match-query-cutoff]] ===== Cutoff frequency The match query supports a `cutoff_frequency` that allows specifying an absolute or relative document frequency where 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 case of an `or` operator or all of the low frequency terms in the case of an `and` operator match. This query allows handling `stopwords` dynamically at runtime, is domain independent and doesn't require a stopword file. It prevents scoring / iterating high frequency terms and only takes the terms into account if a more significant / lower frequency term matches a document. Yet, if all of the query terms are above the given `cutoff_frequency` the query is automatically transformed into a pure conjunction (`and`) query to ensure fast execution. The `cutoff_frequency` can either be relative to the total number of documents if in the range `[0..1)` or absolute if greater or equal to `1.0`. Here is an example showing a query composed of stopwords exclusively: [source,js] -------------------------------------------------- { "match" : { "message" : { "query" : "to be or not to be", "cutoff_frequency" : 0.001 } } } -------------------------------------------------- IMPORTANT: The `cutoff_frequency` option operates on a per-shard-level. This means that when trying it out on test indexes with low document numbers you should follow the advice in {defguide}/relevance-is-broken.html[Relevance is broken]. [[query-dsl-match-query-phrase]] ==== phrase The `match_phrase` query analyzes the text and creates a `phrase` query out of the analyzed text. For example: [source,js] -------------------------------------------------- { "match_phrase" : { "message" : "this is a test" } } -------------------------------------------------- Since `match_phrase` is only a `type` of a `match` query, it can also be used in the following manner: [source,js] -------------------------------------------------- { "match" : { "message" : { "query" : "this is a test", "type" : "phrase" } } } -------------------------------------------------- A phrase query matches terms up to a configurable `slop` (which defaults to 0) in any order. Transposed terms have a slop of 2. The `analyzer` can be set to control which analyzer will perform the analysis process on the text. It defaults to the field explicit mapping definition, or the default search analyzer, for example: [source,js] -------------------------------------------------- { "match_phrase" : { "message" : { "query" : "this is a test", "analyzer" : "my_analyzer" } } } -------------------------------------------------- [[query-dsl-match-query-phrase-prefix]] ==== match_phrase_prefix The `match_phrase_prefix` is the same as `match_phrase`, except that it allows for prefix matches on the last term in the text. For example: [source,js] -------------------------------------------------- { "match_phrase_prefix" : { "message" : "quick brown f" } } -------------------------------------------------- It accepts the same parameters as the phrase type. In addition, it also accepts a `max_expansions` parameter (default `50`) that can control to how many prefixes the last term will be expanded. It is highly recommended to set it to an acceptable value to control the execution time of the query. For example: [source,js] -------------------------------------------------- { "match_phrase_prefix" : { "message" : { "query" : "quick brown f", "max_expansions" : 10 } } } -------------------------------------------------- [IMPORTANT] =================================================== The `match_phrase_prefix` query is a poor-man's autocomplete. It is very easy to use, which let's you get started quickly with _search-as-you-type_ but it's results, which usually are good enough, can sometimes be confusing. Consider the query string `quick brown f`. This query works by creating a phrase query out of `quick` and `brown` (i.e. the term `quick` must exist and must be followed by the term `brown`). Then it looks at the sorted term dictionary to find the first 50 terms that begin with `f`, and adds these terms to the phrase query. The problem is that the first 50 terms may not include the term `fox` so the phase `quick brown fox` will not be found. This usually isn't a problem as the user will continue to type more letters until the word they are looking for appears. For better solutions for _search-as-you-type_ see the <> and {defguide}/_index_time_search_as_you_type.html[Index-Time Search-as-You-Type]. ===================================================