OpenSearch/docs/reference/query-dsl/queries/query-string-syntax.asciidoc

[[query-string-syntax]]

==== Query string syntax

The query string ``mini-language'' is used by the
<<query-dsl-query-string-query>> and by the
`q` query string parameter in the <<search-search,`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

As mentioned in <<query-dsl-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 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 no value (or is missing):

    _missing_:title

* 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*"`.

[WARNING]
======
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`.
======

Wildcarded terms are not analyzed by default -- they are lowercased
(`lowercase_expanded_terms` defaults to `true`) but no further analysis
is done, mainly because it is impossible to accurately analyze a word that
is missing some of its letters.  However, by setting `analyze_wildcard` to
`true`, an attempt will be made to analyze wildcarded words before searching
the term list for matching terms.

===== 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 <<regexp-syntax>>.

[WARNING]
======
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
http://en.wikipedia.org/wiki/Damerau-Levenshtein_distance[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

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..5}


Ranges with one side unbounded can use the following syntax:

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

[NOTE]
===================================================================
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 <<query-dsl-range-filter,`range` filter>>.


===== 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 operators `AND`, `OR` and `NOT` (also written `&&`, `||` and `!`)
are also supported.  However, the effects of these operators can be more
complicated than is obvious at first glance.  `NOT` takes precedence over
`AND`, which takes precedence over `OR`.  While the `+` and `-` only affect
the term to the right of the operator, `AND` and `OR` can affect the terms to
the left and right.

****
Rewriting the above query using `AND`, `OR` and `NOT` demonstrates the
complexity:

`quick OR brown AND fox AND NOT news`::

This is incorrect, because `brown` is now a required term.

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

This is incorrect because at least one of `quick` or `brown` is now required
and the search for those terms would be scored differently from the original
query.

`((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 bares little resemblance to the original.

In contrast, the same query rewritten using the <<query-dsl-match-query,`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`.

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

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

.Watch this space
****
A space may also be a reserved character.  For instance, if you have a
synonym list which converts `"wi fi"` to `"wifi"`, a `query_string` search
for `"wi fi"` would fail. The query string parser would interpret your
query as a search for `"wi OR fi"`, while the token stored in your
index is actually `"wifi"`.  Escaping the space will protect it from
being touched by the query string parser: `"wi\ fi"`.
****

===== Empty Query

If the query string is empty or only contains whitespaces the
query string is interpreted as a `no_docs_query` and will yield
an empty result set.