Returns documents based on a provided query string, using a parser with a strict syntax.

This query uses asyntax to parse and split the provided query string based on operators, such asAND orNOT. The query thenanalyzes each split text independently before returning matching documents.

You can use thequery_string query to create a complex search that includes wildcard characters, searches across multiple fields, and more. While versatile, the query is strict and returns an error if the query string includes any invalid syntax.

When running the following search, thequery_string query splits(new york city) OR (big apple) into two parts:new york city andbig apple. Thecontent field’s analyzer then independently converts each part into tokens before returning matching documents. Because the query syntax does not use whitespace as an operator,new york city is passed as-is to the analyzer.

GET /_search{  "query": {    "query_string": {      "query": "(new york city) OR (big apple)",      "default_field": "content"    }  }}

query

(Required, string) Query string you wish to parse and use for search. SeeQuery string syntax.

default_field

(Optional, string) Default field to search if no field is provided in the query string. Supports wildcards (*).

Defaults to theindex.query.default_field index setting, which has a default value of*. The* value extracts all fields that are eligible for term queries and filters the metadata fields. All extracted fields are then combined to build a query if noprefix is specified.

Searching across all eligible fields does not includenested documents. Use anested query to search those documents.

allow_leading_wildcard

(Optional, Boolean) Iftrue, the wildcard characters* and? are allowed as the first character of the query string. Defaults totrue.

analyze_wildcard

(Optional, Boolean) Iftrue, the query attempts to analyze wildcard terms in the query string. Defaults tofalse. Note that, in case oftrue, only queries that end with a*are fully analyzed. Queries that start with* or have it in the middleare onlynormalized.

analyzer

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

auto_generate_synonyms_phrase_query

(Optional, Boolean) Iftrue,match phrase queries are automatically created for multi-term synonyms. Defaults totrue. SeeSynonyms and thequery_string query for an example.

boost

(Optional, float) Floating point number used to decrease or increase therelevance scores of the query. Defaults to1.0.

Boost values are relative to the default value of1.0. A boost value between0 and1.0 decreases the relevance score. A value greater than1.0 increases the relevance score.

default_operator

(Optional, string) Default boolean logic used to interpret text in the query string if no operators are specified. Valid values are:

• OR (Default)For example, a query string ofcapital of Hungary is interpreted ascapital OR of OR Hungary.
• ANDFor example, a query string ofcapital of Hungary is interpreted ascapital AND of AND Hungary.

enable_position_increments

(Optional, Boolean) Iftrue, enable position increments in queries constructed from aquery_string search. Defaults totrue.

fields

(Optional, array of strings) Array of fields to search. Supports wildcards (*).

You can use this parameter query to search across multiple fields. SeeSearch multiple fields.

fuzziness

(Optional, string) Maximum edit distance allowed for fuzzy matching. For fuzzy syntax, seeFuzziness.

fuzzy_max_expansions

(Optional, integer) Maximum number of terms to which the query expands for fuzzy matching. Defaults to50.

fuzzy_prefix_length

(Optional, integer) Number of beginning characters left unchanged for fuzzy matching. Defaults to0.

fuzzy_transpositions

(Optional, Boolean) Iftrue, edits for fuzzy matching include transpositions of two adjacent characters (ab → ba). Defaults totrue.

lenient

(Optional, Boolean) Iftrue, format-based errors, such as providing a text value for anumeric field, are ignored. Defaults tofalse.

max_determinized_states

(Optional, integer) Maximum number ofautomaton states required for the query. Default is10000.

Elasticsearch usesApache Lucene internally to parse regular expressions. Lucene converts each regular expression to a finite automaton containing a number of determinized states.

You can use this parameter to prevent that conversion from unintentionally consuming too many resources. You may need to increase this limit to run complex regular expressions.

minimum_should_match

(Optional, string) Minimum number of clauses that must match for a document to be returned. See theminimum_should_match parameter for valid values and more information. SeeHowminimum_should_match works for an example.

quote_analyzer

(Optional, string)Analyzer used to convert quoted text in the query string into tokens. Defaults to thesearch_quote_analyzer mapped for thedefault_field.

For quoted text, this parameter overrides the analyzer specified in theanalyzer parameter.

phrase_slop

(Optional, integer) Maximum number of positions allowed between matching tokens for phrases. Defaults to0. If0, exact phrase matches are required. Transposed terms have a slop of2.

quote_field_suffix

(Optional, string) Suffix appended to quoted text in the query string.

You can use this suffix to use a different analysis method for exact matches. SeeMixing exact search with stemming.

rewrite

(Optional, string) Method used to rewrite the query. For valid values and more information, see therewrite parameter.

time_zone

(Optional, string)Coordinated Universal Time (UTC) offset orIANA time zone used to convertdate values in the query string to UTC.

Valid values are ISO 8601 UTC offsets, such as+01:00 or -08:00, and IANA time zone IDs, such asAmerica/Los_Angeles.

The query string mini-language is used by the Query string and by theq query string parameter in thesearch API.

The query string is parsed into a series ofterms andoperators. A term can be a single word —quick orbrown — or a phrase, surrounded by double quotes —"quick brown" — which searches for all the words in the phrase, in the same order.

Operators allow you to customize the search — the available options are explained below.

You can specify fields to search in the query syntax:

• where thestatus field containsactive

  status:active

• where thetitle field containsquick orbrown

  title:(quick OR brown)

• where theauthor field contains the exact phrase"john smith"

  author:"John Smith"

• where thefirst name field containsAlice (note how we need to escape the space with a backslash)

  first\ name:Alice

• where any of the fieldsbook.title,book.content orbook.date containsquick orbrown (note how we need to escape the* with a backslash):

  book.\*:(quick OR brown)

• where the fieldtitle has any non-null value:

  _exists_:title

Wildcard searches can be run on individual terms, using? to replace a single character, and* to replace zero or more characters:

qu?ck bro*

Be aware that wildcard queries can use an enormous amount of memory and perform very badly — just think how many terms need to be queried to match the query string"a* b* c*".

{  "field": ""}

{  "field": null}

Only parts of the analysis chain that operate at the character level are applied. So for instance, if the analyzer performs both lowercasing and stemming, only the lowercasing will be applied: it would be wrong to perform stemming on a word that is missing some of its letters.

By settinganalyze_wildcard to true, queries that end with a* will be analyzed and a boolean query will be built out of the different tokens, by ensuring exact matches on the first N-1 tokens, and prefix match on the last token.

Regular expression patterns can be embedded in the query string by wrapping them in forward-slashes ("/"):

name:/joh?n(ath[oa]n)/

The supported regular expression syntax is explained inRegular expression syntax.

/.*n/

You can runfuzzy queries using the~ operator:

quikc~ brwn~ foks~

For these queries, the query string isnormalized. If present, only certain filters from the analyzer are applied. For a list of applicable filters, seeNormalizers.

The query uses theDamerau-Levenshtein distance to find all terms with a maximum of two changes, where a change is the insertion, deletion or substitution of a single character, or transposition of two adjacent characters.

The defaultedit distance is2, but an edit distance of1 should be sufficient to catch 80% of all human misspellings. It can be specified as:

quikc~1

While a phrase query (eg"john smith") expects all of the terms in exactly the same order, a proximity query allows the specified words to be further apart or in a different order. In the same way that fuzzy queries can specify a maximum edit distance for characters in a word, a proximity search allows us to specify a maximum edit distance of words in a phrase:

"fox quick"~5

The closer the text in a field is to the original order specified in the query string, the more relevant that document is considered to be. When compared to the above example query, the phrase"quick fox" would be considered more relevant than"quick brown fox".

Ranges can be specified for date, numeric or string fields. Inclusive ranges are specified with square brackets[min TO max] and exclusive ranges with curly brackets{min TO max}.

• All days in 2012:

  date:[2012-01-01 TO 2012-12-31]

• Numbers 1..5

  count:[1 TO 5]

• Tags betweenalpha andomega, excludingalpha andomega:

  tag:{alpha TO omega}

• Numbers from 10 upwards

  count:[10 TO *]

• Dates before 2012

  date:{* TO 2012-01-01}

Curly and square brackets can be combined:

• Numbers from 1 up to but not including 5

  count:[1 TO 5}

Ranges with one side unbounded can use the following syntax:

age:>10age:>=10age:<10age:<=10

age:(>=10 AND <20)age:(+>=10 +<20)

The parsing of ranges in query strings can be complex and error prone. It is much more reliable to use an explicitrange query.

Use theboost operator^ to make one term more relevant than another. For instance, if we want to find all documents about foxes, but we are especially interested in quick foxes:

quick^2 fox

The defaultboost value is 1, but can be any positive floating point number. Boosts between 0 and 1 reduce relevance.

Boosts can also be applied to phrases or to groups:

"john smith"^2   (foo bar)^4

By default, all terms are optional, as long as one term matches. A search forfoo bar baz will find any document that contains one or more offoo orbar orbaz. We have already discussed thedefault_operator above which allows you to force all terms to be required, but there are alsoboolean operators which can be used in the query string itself to provide more control.

The preferred operators are+ (this termmust be present) and- (this termmust not be present). All other terms are optional. For example, this query:

quick brown +fox -news

states that:

• fox must be present
• news must not be present
• quick andbrown are optional — their presence increases the relevance

The familiar boolean operatorsAND,OR andNOT (also written&&,|| and!) are also supported but beware that they do not honor the usual precedence rules, so parentheses should be used whenever multiple operators are used together. For instance the previous query could be rewritten as:

((quick AND fox) OR (brown AND fox) OR fox) AND NOT news

This form now replicates the logic from the original query correctly, but the relevance scoring bears little resemblance to the original.

In contrast, the same query rewritten using thematch query would look like this:

{    "bool": {        "must":     { "match": "fox"         },        "should":   { "match": "quick brown" },        "must_not": { "match": "news"        }    }}

Multiple terms or clauses can be grouped together with parentheses, to form sub-queries:

(quick OR brown) AND fox

Groups can be used to target a particular field, or to boost the result of a sub-query:

status:(active OR pending) title:(full text search)^2

If you need to use any of the characters which function as operators in your query itself (and not as operators), then you should escape them with a leading backslash. For instance, to search for(1+1)=2, you would need to write your query as\(1\+1\)\=2. When using JSON for the request body, two preceding backslashes (\\) are required; the backslash is a reserved escaping character in JSON strings.

GET /my-index-000001/_search{  "query" : {    "query_string" : {      "query" : "kimchy\\!",      "fields"  : ["user.id"]    }  }}

The reserved characters are:+ - = && || > < ! ( ) { } [ ] ^ " ~ * ? : \ /

Failing to escape these special characters correctly could lead to a syntax error which prevents your query from running.

Whitespace is not considered an operator.

If the query string is empty or only contains whitespaces the query will yield an empty result set.

query_string searches do not returnnested documents. To search nested documents, use thenested query.

You can use thefields parameter to perform aquery_string search across multiple fields.

The idea of running thequery_string query against multiple fields is to expand each query term to an OR clause like this:

field1:query_term OR field2:query_term | ...

For example, the following query

GET /_search{  "query": {    "query_string": {      "fields": [ "content", "name" ],      "query": "this AND that"    }  }}

matches the same words as

GET /_search{  "query": {    "query_string": {      "query": "(content:this OR name:this) AND (content:that OR name:that)"    }  }}

Since several queries are generated from the individual search terms, combining them is automatically done using adis_max query with atie_breaker. For example (thename is boosted by 5 using^5 notation):

GET /_search{  "query": {    "query_string" : {      "fields" : ["content", "name^5"],      "query" : "this AND that OR thus",      "tie_breaker" : 0    }  }}

Simple wildcard can also be used to search "within" specific inner elements of the document. For example, if we have acity object with several fields (or inner object with fields) in it, we can automatically search on all "city" fields:

GET /_search{  "query": {    "query_string" : {      "fields" : ["city.*"],      "query" : "this AND that OR thus"    }  }}

Another option is to provide the wildcard fields search in the query string itself (properly escaping the* sign), for example:city.\*:something:

GET /_search{  "query": {    "query_string" : {      "query" : "city.\\*:(this AND that OR thus)"    }  }}

The fields parameter can also include pattern based field names, allowing to automatically expand to the relevant fields (dynamically introduced fields included). For example:

GET /_search{  "query": {    "query_string" : {      "fields" : ["content", "name.*^5"],      "query" : "this AND that OR thus"    }  }}

When running thequery_string query against multiple fields, the following additional parameters are supported.

type

(Optional, string) Determines how the query matches and scores documents. Valid values are:

best_fields (Default)

Finds documents which match any field and uses the highest_score from any matching field. Seebest_fields.

bool_prefix

Creates amatch_bool_prefix query on each field and combines the_score from each field. Seebool_prefix.

cross_fields

Treats fields with the sameanalyzer as though they were one big field. Looks for each word inany field. Seecross_fields.

most_fields

Finds documents which match any field and combines the_score from each field. Seemost_fields.

phrase

Runs amatch_phrase query on each field and uses the_score from the best field. Seephrase andphrase_prefix.

phrase_prefix

Runs amatch_phrase_prefix query on each field and uses the_score from the best field. Seephrase andphrase_prefix.

NOTE: Additional top-levelmulti_match parameters may be available based on thetype value.

Thequery_string query supports multi-terms synonym expansion with thesynonym_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": {       "query_string" : {           "default_field": "title",           "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 termny or the conjunctionnew AND york. By default the parameterauto_generate_synonyms_phrase_query is set totrue.

Thequery_string splits the query around each operator to create a boolean query for the entire input. You can useminimum_should_match to control how many "should" clauses in the resulting query should match.

GET /_search{  "query": {    "query_string": {      "fields": [        "title"      ],      "query": "this that thus",      "minimum_should_match": 2    }  }}

The example above creates a boolean query:

(title:this title:that title:thus)~2

that matches documents with at least two of the termsthis,that orthus in the single fieldtitle.

GET /_search{  "query": {    "query_string": {      "fields": [        "title",        "content"      ],      "query": "this that thus",      "minimum_should_match": 2    }  }}

The example above creates a boolean query:

((content:this content:that content:thus) | (title:this title:that title:thus))

that matches documents with the disjunction max over the fieldstitle andcontent. Here theminimum_should_match parameter can’t be applied.

GET /_search{  "query": {    "query_string": {      "fields": [        "title",        "content"      ],      "query": "this OR that OR thus",      "minimum_should_match": 2    }  }}

Adding explicit operators forces each term to be considered as a separate clause.

The example above creates a boolean query:

((content:this | title:this) (content:that | title:that) (content:thus | title:thus))~2

that matches documents with at least two of the three "should" clauses, each of them made of the disjunction max over the fields for each term.

Across_fields value in thetype field indicates fields with the same analyzer are grouped together when the input is analyzed.

GET /_search{  "query": {    "query_string": {      "fields": [        "title",        "content"      ],      "query": "this OR that OR thus",      "type": "cross_fields",      "minimum_should_match": 2    }  }}

The example above creates a boolean query:

(blended(terms:[field2:this, field1:this]) blended(terms:[field2:that, field1:that]) blended(terms:[field2:thus, field1:thus]))~2

that matches documents with at least two of the three per-term blended queries.

Query string query can be internally be transformed to aprefix query which means that if the prefix queries are disabled as explainedhere the query will not be executed and an exception will be thrown.