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Query String Query

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Query String Query

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A query that uses a query parser in order to parse its content. Here is an example:

GET /_search
{
    "query": {
        "query_string" : {
            "default_field" : "content",
            "query" : "this AND that OR thus"
        }
    }
}

The query_string query parses the input and splits text around operators. Each textual part is analyzed independently of each other. For instance the following query:

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

will be split into new york city and big apple and each part is then analyzed independently by the analyzer configured for the field.

Whitespaces are not considered operators, this means that new york city will be passed "as is" to the analyzer configured for the field. If the field is a keyword field the analyzer will create a single term new york city and the query builder will use this term in the query. If you want to query each term separately you need to add explicit operators around the terms (e.g. new AND york AND city).

When multiple fields are provided it is also possible to modify how the different field queries are combined inside each textual part using the type parameter. The possible modes are described here and the default is best_fields.

The query_string top level parameters include:

Parameter	Description
`query`	The actual query to be parsed. See Query string syntax.
`default_field`	The default field for query terms if no prefix field is specified. Defaults to the `index.query.default_field` index settings, which in turn defaults to ``. `` extracts all fields in the mapping that are eligible to term queries and filters the metadata fields. All extracted fields are then combined to build a query when no prefix field is provided. WARNING: In future versions (starting in 7.0), there will be a limit on the number of fields that can be queried at once. This limit will be determined by the `indices.query.bool.max_clause_count` setting which defaults to 1024. Currently this will be raised and logged as a Warning only.
`default_operator`	The default operator used if no explicit operator is specified. For example, with a default operator of `OR`, the query `capital of Hungary` is translated to `capital OR of OR Hungary`, and with default operator of `AND`, the same query is translated to `capital AND of AND Hungary`. The default value is `OR`.
`analyzer`	The analyzer name used to analyze the query string.
`quote_analyzer`	The name of the analyzer that is used to analyze quoted phrases in the query string. For those parts, it overrides other analyzers that are set using the `analyzer` parameter or the `search_quote_analyzer` setting.
`allow_leading_wildcard`	When set, `*` or `?` are allowed as the first character. Defaults to `true`.
`enable_position_increments`	Set to `true` to enable position increments in result queries. Defaults to `true`.
`fuzzy_max_expansions`	Controls the number of terms fuzzy queries will expand to. Defaults to `50`
`fuzziness`	Set the fuzziness for fuzzy queries. Defaults to `AUTO`. See Fuzziness for allowed settings.
`fuzzy_prefix_length`	Set the prefix length for fuzzy queries. Default is `0`.
`fuzzy_transpositions`	Set to `false` to disable fuzzy transpositions (`ab` → `ba`). Default is `true`.
`phrase_slop`	Sets the default slop for phrases. If zero, then exact phrase matches are required. Default value is `0`.
`boost`	Sets the boost value of the query. Defaults to `1.0`.
`auto_generate_phrase_queries`	Deprecated setting. This setting is ignored, use [type=phrase] instead to make phrase queries out of all text that is within query operators, or use explicitly quoted strings if you need finer-grained control.
`analyze_wildcard`	By default, wildcards terms in a query string are not analyzed. By setting this value to `true`, a best effort will be made to analyze those as well.
`max_determinized_states`	Limit on how many automaton states regexp queries are allowed to create. This protects against too-difficult (e.g. exponentially hard) regexps. Defaults to 10000.
`minimum_should_match`	A value controlling how many "should" clauses in the resulting boolean query should match. It can be an absolute value (`2`), a percentage (`30%`) or a combination of both.
`lenient`	If set to `true` will cause format based failures (like providing text to a numeric field) to be ignored.
`time_zone`	Time Zone to be applied to any range query related to dates. See also JODA timezone.
`quote_field_suffix`	A suffix to append to fields for quoted parts of the query string. This allows to use a field that has a different analysis chain for exact matching. Look here for a comprehensive example.
`auto_generate_synonyms_phrase_query`	Whether phrase queries should be automatically generated for multi terms synonyms. Defaults to `true`.
`all_fields`	[6.0.0] Deprecated in 6.0.0. set `default_field` to `*` instead Perform the query on all fields detected in the mapping that can be queried. Will be used by default when the `_all` field is disabled and no `default_field` is specified (either in the index settings or in the request body) and no `fields` are specified.

When a multi term query is being generated, one can control how it gets rewritten using the rewrite parameter.

Default Field

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When not explicitly specifying the field to search on in the query string syntax, the index.query.default_field will be used to derive which field to search on. If the index.query.default_field is not specified, the query_string will automatically attempt to determine the existing fields in the index’s mapping that are queryable, and perform the search on those fields. This will not include nested documents, use a nested query to search those documents.

For mappings with a large number of fields, searching across all queryable fields in the mapping could be expensive.

Multi Field

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The query_string query can also run against multiple fields. Fields can be provided via the fields parameter (example below).

The idea of running the query_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 a dis_max query with a tie_breaker. For example (the name 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 a city 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)"
        }
    }
}

Since \ (backslash) is a special character in json strings, it needs to be escaped, hence the two backslashes in the above query_string.

When running the query_string query against multiple fields, the following additional parameters are allowed:

Parameter	Description
`type`	How the fields should be combined to build the text query. See types for a complete example. Defaults to `best_fields`
`tie_breaker`	The disjunction max tie breaker for multi fields. Defaults to `0`

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"
        }
    }
}

Synonyms

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The query_string 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": {
       "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 term ny or the conjunction new AND york. By default the parameter auto_generate_synonyms_phrase_query is set to true.

Minimum should match

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The query_string splits the query around each operator to create a boolean query for the entire input. You can use minimum_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 terms this, that or thus in the single field title.

Multi Field

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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 fields title and content. Here the minimum_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.

Cross Field

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

The cross_fields value in the type field indicates that fields that have the same analyzer should be grouped together when the input is analyzed.

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 syntax

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The query string “mini-language” is used by the Query String Query and by the q query string parameter in the search API.

The query string is parsed into a series of terms and operators. A term can be a single word — quick or brown — 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.

Field names

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As mentioned in Query String Query, the default_field is searched for the search terms, but it is possible to specify other fields in the query syntax:

where the status field contains active
```
status:active
```
where the title field contains quick or brown. If you omit the OR operator the default operator will be used
```
title:(quick OR brown)
title:(quick brown)
```
where the author field contains the exact phrase "john smith"
```
author:"John Smith"
```
where the first name field contains Alice (note how we need to escape the space with a backslash)
```
first\ name:Alice
```
where any of the fields book.title, book.content or book.date contains quick or brown (note how we need to escape the * with a backslash):
```
book.\*:(quick brown)
```
where the field title has any non-null value:
```
_exists_:title
```

Wildcards

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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*".

Pure wildcards \* are rewritten to exists queries for efficiency. As a consequence, the wildcard "field:*" would match documents with an empty value like the following:

{
  "field": ""
}

... and would not match if the field is missing or set with an explicit null value like the following:

{
  "field": null
}

Allowing a wildcard at the beginning of a word (eg "*ing") is particularly heavy, because all terms in the index need to be examined, just in case they match. Leading wildcards can be disabled by setting allow_leading_wildcard to false.

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 setting analyze_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 expressions

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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 in Regular expression syntax.

The allow_leading_wildcard parameter does not have any control over regular expressions. A query string such as the following would force Elasticsearch to visit every term in the index:

/.*n/

Use with caution!

Fuzziness

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We can search for terms that are similar to, but not exactly like our search terms, using the “fuzzy” operator:

quikc~ brwn~ foks~

This uses the Damerau-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 default edit distance is 2, but an edit distance of 1 should be sufficient to catch 80% of all human misspellings. It can be specified as:

quikc~1

Proximity searches

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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

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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 between alpha and omega, excluding alpha and omega:
```
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:>10
age:>=10
age:<10
age:<=10

To combine an upper and lower bound with the simplified syntax, you would need to join two clauses with an AND operator:

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 explicit range query.

Boosting

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Use the boost 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 default boost 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

Boolean operators

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

The preferred operators are + (this term must be present) and - (this term must 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 and brown are optional — their presence increases the relevance

The familiar boolean operators AND, OR and NOT (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 the match query would look like this:

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

Grouping

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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

Reserved characters

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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 /twitter/_search
{
  "query" : {
    "query_string" : {
      "query" : "kimchy\\!",
      "fields"  : ["user"]
    }
  }
}

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

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

< and > can’t be escaped at all. The only way to prevent them from attempting to create a range query is to remove them from the query string entirely.

Empty Query

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

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