OpenSearch/docs/reference/query-dsl/match-query.asciidoc

[[query-dsl-match-query]]
=== Match Query


`match` queries accept text/numerics/dates, analyzes
them, and constructs a query. For example:

[source,js]
--------------------------------------------------
GET /_search
{
    "query": {
        "match" : {
            "message" : "this is a test"
        }
    }
}
--------------------------------------------------
// CONSOLE

Note, `message` is the name of a field, you can substitute the name of
any field instead.

[[query-dsl-match-query-boolean]]
==== match

The `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
<<query-dsl-minimum-should-match,`minimum_should_match`>>
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 <<fuzziness>> 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 <<query-dsl-multi-term-rewrite,rewrite
method>> 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`.

Note that fuzzy matching is not applied to terms with synonyms, as under the hood
these terms are expanded to a special synonym query that blends term frequencies,
which does not support fuzzy expansion.

Here is an example when providing additional parameters (note the slight
change in structure, `message` is the field name):

[source,js]
--------------------------------------------------
GET /_search
{
    "query": {
        "match" : {
            "message" : {
                "query" : "this is a test",
                "operator" : "and"
            }
        }
    }
}
--------------------------------------------------
// CONSOLE

[[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]
--------------------------------------------------
GET /_search
{
    "query": {
        "match" : {
            "message" : {
                "query" : "to be or not to be",
                "operator" : "and",
                "zero_terms_query": "all"
            }
        }
    }
}
--------------------------------------------------
// CONSOLE

[[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]
--------------------------------------------------
GET /_search
{
    "query": {
        "match" : {
            "message" : {
                "query" : "to be or not to be",
                "cutoff_frequency" : 0.001
            }
        }
    }
}
--------------------------------------------------
// CONSOLE

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-synonyms]]
===== Synonyms

The `match` query supports multi-terms synonym expansion with the <<analysis-synonym-graph-tokenfilter,
synonym_graph>> token filter. When this filter is used, the parser creates a phrase query for each multi-terms synonyms.
For example, the following synonym: `"ny, new york" would produce:`

`(ny OR ("new york"))`

It is also possible to match multi terms synonyms with conjunctions instead:

[source,js]
--------------------------------------------------
GET /_search
{
   "query": {
       "match" : {
           "message": {
               "query" : "ny city",
               "auto_generate_synonyms_phrase_query" : false
           }
       }
   }
}
--------------------------------------------------
// CONSOLE

The example above creates a boolean query:

`(ny OR (new AND york)) city`

that matches documents with the term `ny` or the conjunction `new AND york`.
By default the parameter `auto_generate_synonyms_phrase_query` is set to `true`.


.Comparison to query_string / field
**************************************************

The match family of queries does not go through a "query parsing"
process. It does not support field name prefixes, wildcard characters,
or other "advanced" features. For this reason, chances of it failing are
very small / non existent, and it provides an excellent behavior when it
comes to just analyze and run that text as a query behavior (which is
usually what a text search box does).

**************************************************