Match query

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Returns documents that match a provided text, number, date or boolean value. The provided text is analyzed before matching.

The match query is the standard query for performing a full-text search, including options for fuzzy matching.

Example request

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GET /_search
{
  "query": {
    "match": {
      "message": {
        "query": "this is a test"
      }
    }
  }
}

Top-level parameters for match

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<field>
(Required, object) Field you wish to search.

Parameters for <field>

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query

(Required) Text, number, boolean value or date you wish to find in the provided <field>.

The match query analyzes any provided text before performing a search. This means the match query can search text fields for analyzed tokens rather than an exact term.

analyzer
(Optional, string) Analyzer used to convert the text in the query value into tokens. Defaults to the index-time analyzer mapped for the <field>. If no analyzer is mapped, the index’s default analyzer is used.
auto_generate_synonyms_phrase_query

(Optional, Boolean) If true, match phrase queries are automatically created for multi-term synonyms. Defaults to true.

See Use synonyms with match query for an example.

fuzziness
(Optional, string) Maximum edit distance allowed for matching. See Fuzziness for valid values and more information. See Fuzziness in the match query for an example.
max_expansions
(Optional, integer) Maximum number of terms to which the query will expand. Defaults to 50.
prefix_length
(Optional, integer) Number of beginning characters left unchanged for fuzzy matching. Defaults to 0.
fuzzy_transpositions
(Optional, Boolean) If true, edits for fuzzy matching include transpositions of two adjacent characters (ab → ba). Defaults to true.
fuzzy_rewrite

(Optional, string) Method used to rewrite the query. See the rewrite parameter for valid values and more information.

If the fuzziness parameter is not 0, the match query uses a fuzzy_rewrite method of top_terms_blended_freqs_${max_expansions} by default.

lenient
(Optional, Boolean) If true, format-based errors, such as providing a text query value for a numeric field, are ignored. Defaults to false.
operator

(Optional, string) Boolean logic used to interpret text in the query value. Valid values are:

OR (Default)
For example, a query value of capital of Hungary is interpreted as capital OR of OR Hungary.
AND
For example, a query value of capital of Hungary is interpreted as capital AND of AND Hungary.
minimum_should_match

(Optional, string) Minimum number of clauses that must match for a document to be returned. See the minimum_should_match parameter for valid values and more information.

zero_terms_query

(Optional, string) Indicates whether no documents are returned if the analyzer removes all tokens, such as when using a stop filter. Valid values are:

none (Default)
No documents are returned if the analyzer removes all tokens.
all
Returns all documents, similar to a match_all query.

See Zero terms query for an example.

Notes

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Short request example

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You can simplify the match query syntax by combining the <field> and query parameters. For example:

GET /_search
{
  "query": {
    "match": {
      "message": "this is a test"
    }
  }
}

How the match query works

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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 parameter 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 minimum_should_match parameter.

Here is an example with the operator parameter:

GET /_search
{
  "query": {
    "match": {
      "message": {
        "query": "this is a test",
        "operator": "and"
      }
    }
  }
}

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.

Fuzziness in the match query

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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 rewrite method the fuzzy_rewrite parameter allows to control how the query will get rewritten.

Fuzzy transpositions (abba) are allowed by default but can be disabled by setting fuzzy_transpositions to false.

Fuzzy matching is not applied to terms with synonyms or in cases where the analysis process produces multiple tokens at the same position. Under the hood these terms are expanded to a special synonym query that blends term frequencies, which does not support fuzzy expansion.

GET /_search
{
  "query": {
    "match": {
      "message": {
        "query": "this is a testt",
        "fuzziness": "AUTO"
      }
    }
  }
}

Zero terms query

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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.

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

Cutoff frequency

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Deprecated in 7.3.0.

This option can be omitted as the Match can skip blocks of documents efficiently, without any configuration, provided that the total number of hits is not tracked.

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 from 0 (inclusive) to 1 (exclusive) or absolute if greater or equal to 1.0.

Here is an example showing a query composed of stopwords exclusively:

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

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 Relevance is broken.

Synonyms

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The match query supports multi-terms synonym expansion with the 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:

GET /_search
{
   "query": {
       "match" : {
           "message": {
               "query" : "ny city",
               "auto_generate_synonyms_phrase_query" : false
           }
       }
   }
}

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.