Full text queries - Query string - 《Elasticsearch v7.9 Reference》

Query string query

Query string query

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

This query uses a syntax to parse and split the provided query string based on operators, such as AND or NOT. The query then analyzes each split text independently before returning matching documents.

You can use the query_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.

Because it returns an error for any invalid syntax, we don’t recommend using the query_string query for search boxes.

If you don’t need to support a query syntax, consider using the match query. If you need the features of a query syntax, use the simple_query_string query, which is less strict.

Example request

When running the following search, the query_string query splits (new york city) OR (big apple) into two parts: new york city and big apple. The content 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"
    }
  }
}

Top-level parameters for `query_string`

query

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

default_field

(Optional, string) Default field you wish to search if no field is provided in the query string.

Defaults to the index.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 no prefix is specified.

Searching across all eligible fields does not include nested documents. Use a nested query to search those documents.

For mappings with a large number of fields, searching across all eligible fields could be expensive.

There is a limit on the number of fields that can be queried at once. It is defined by the indices.query.bool.max_clause_count search setting, which defaults to 1024.

allow_leading_wildcard

(Optional, boolean) If true, the wildcard characters * and ? are allowed as the first character of the query string. Defaults to true.

analyze_wildcard

(Optional, boolean) If true, the query attempts to analyze wildcard terms in the query string. Defaults to false.

analyzer

(Optional, string) Analyzer used to convert text in the query string into tokens. Defaults to the index-time analyzer mapped for the default_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 Synonyms and the query_string query for an example.

boost

(Optional, float) Floating point number used to decrease or increase the relevance scores of the query. Defaults to 1.0.

Boost values are relative to the default value of 1.0. A boost value between 0 and 1.0 decreases the relevance score. A value greater than 1.0 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 of capital of Hungary is interpreted as capital OR of OR Hungary.

AND

For example, a query string of capital of Hungary is interpreted as capital AND of AND Hungary.

enable_position_increments

(Optional, boolean) If true, enable position increments in queries constructed from a query_string search. Defaults to true.

fields

(Optional, array of strings) Array of fields you wish to search.

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

fuzziness

(Optional, string) Maximum edit distance allowed for matching. See Fuzziness for valid values and more information.

fuzzy_max_expansions

(Optional, integer) Maximum number of terms to which the query expands for fuzzy matching. Defaults to 50.

fuzzy_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.

lenient

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

max_determinized_states

(Optional, integer) Maximum number of automaton states required for the query. Default is 10000.

Elasticsearch uses Apache 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 the minimum_should_match parameter for valid values and more information. See How minimum_should_match works for an example.

quote_analyzer

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

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

phrase_slop

(Optional, integer) Maximum number of positions allowed between matching tokens for phrases. Defaults to 0. If 0, exact phrase matches are required. Transposed terms have a slop of 2.

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. See Mixing exact search with stemming.

rewrite

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

time_zone

(Optional, string) Coordinated Universal Time (UTC) offset or IANA time zone used to convert date 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 as America/Los_Angeles.

The time_zone parameter does not affect the date math value of now. now is always the current system time in UTC. However, the time_zone parameter does convert dates calculated using now and date math rounding. For example, the time_zone parameter will convert a value of now/d.

Notes

Query string syntax

The query string “mini-language” is used by the Query string 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

You can specify fields to search in the query syntax:

where the status field contains active
```
status:active
```
where the title field contains quick or brown
```
title:(quick OR 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 OR brown)
```
where the field title has any non-null value:
```
_exists_:title
```

Wildcards

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

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

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

Avoid mixing fuzziness with wildcards

Mixing fuzzy and wildcard operators is not supported. When mixed, one of the operators is not applied. For example, you can search for app~1 (fuzzy) or app* (wildcard), but searches for app*~1 do not apply the fuzzy operator (~1).

Proximity searches

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

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

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

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

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

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.

< 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.

Whitespaces and empty queries

Whitespace is not considered an operator.

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

Avoid using the `query_string` query for nested documents

query_string searches do not return nested documents. To search nested documents, use the nested query.

Search multiple fields

You can use the fields parameter to perform a query_string search across multiple fields.

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.

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"
    }
  }
}

Additional parameters for multiple field searches

When running the query_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. See best_fields.

bool_prefix

Creates a match_bool_prefix query on each field and combines the _score from each field. See bool_prefix.

cross_fields

Treats fields with the same analyzer as though they were one big field. Looks for each word in any field. See cross_fields.

most_fields

Finds documents which match any field and combines the _score from each field. See most_fields.

phrase

Runs a match_phrase query on each field and uses the _score from the best field. See phrase and phrase_prefix.

phrase_prefix

Runs a match_phrase_prefix query on each field and uses the _score from the best field. See phrase and phrase_prefix.

NOTE: Additional top-level multi_match parameters may be available based on the type value.

Synonyms and the `query_string` query

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
       }
   }
}