[[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 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`.
=======

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 <<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 TO 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-query,`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 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 bears 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.

NOTE: `<` 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.

.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"`.  The option `split_on_whitespace=false` will protect it from
being touched by the query string parser and will let the analysis run on the entire input (`"wi fi"`).
****

===== Empty Query

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