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

252 lines
8.0 KiB
Plaintext

[[query-dsl-query-string-query]]
=== Query String Query
A query that uses a query parser in order to parse its content. Here is
an example:
[source,js]
--------------------------------------------------
GET /_search
{
"query": {
"query_string" : {
"default_field" : "content",
"query" : "this AND that OR thus"
}
}
}
--------------------------------------------------
// CONSOLE
The `query_string` top level parameters include:
[cols="<,<",options="header",]
|=======================================================================
|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 `_all`.
|`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.
|`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`.
|`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` |Defaults to `false`.
|`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
<<query-dsl-minimum-should-match,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
http://www.joda.org/joda-time/apidocs/org/joda/time/DateTimeZone.html[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 <<mixing-exact-search-with-stemming,here>> for a
comprehensive example.
|`split_on_whitespace` |Whether query text should be split on whitespace prior to analysis.
Instead the queryparser would parse around only real 'operators'. Default to `false`.
It is not allowed to set this option to `false` if `autoGeneratePhraseQueries` is already set to `true`.
|`all_fields` | 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
<<query-dsl-multi-term-rewrite,rewrite>>
parameter.
[float]
==== Default Field
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. It defaults to `_all` field.
If the `_all` field is disabled, the `query_string` query will automatically
attempt to determine the existing fields in the index's mapping that are
queryable, and perform the search on those fields. Note that this will not
include nested documents, use a nested query to search those documents.
[float]
==== Multi Field
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
[source,js]
--------------------------------------------------
GET /_search
{
"query": {
"query_string" : {
"fields" : ["content", "name"],
"query" : "this AND that"
}
}
}
--------------------------------------------------
// CONSOLE
matches the same words as
[source,js]
--------------------------------------------------
GET /_search
{
"query": {
"query_string": {
"query": "(content:this OR name:this) AND (content:that OR name:that)"
}
}
}
--------------------------------------------------
// CONSOLE
Since several queries are generated from the individual search terms,
combining them can be automatically done using either a `dis_max` query or a
simple `bool` query. For example (the `name` is boosted by 5 using `^5`
notation):
[source,js]
--------------------------------------------------
GET /_search
{
"query": {
"query_string" : {
"fields" : ["content", "name^5"],
"query" : "this AND that OR thus",
"use_dis_max" : true
}
}
}
--------------------------------------------------
// CONSOLE
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:
[source,js]
--------------------------------------------------
GET /_search
{
"query": {
"query_string" : {
"fields" : ["city.*"],
"query" : "this AND that OR thus",
"use_dis_max" : true
}
}
}
--------------------------------------------------
// CONSOLE
Another option is to provide the wildcard fields search in the query
string itself (properly escaping the `*` sign), for example:
`city.\*:something`:
[source,js]
--------------------------------------------------
GET /_search
{
"query": {
"query_string" : {
"query" : "city.\\*:(this AND that OR thus)",
"use_dis_max" : true
}
}
}
--------------------------------------------------
// CONSOLE
NOTE: 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:
[cols="<,<",options="header",]
|=======================================================================
|Parameter |Description
|`use_dis_max` |Should the queries be combined using `dis_max` (set it
to `true`), or a `bool` query (set it to `false`). Defaults to `true`.
|`tie_breaker` |When using `dis_max`, the disjunction max tie breaker.
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:
[source,js]
--------------------------------------------------
GET /_search
{
"query": {
"query_string" : {
"fields" : ["content", "name.*^5"],
"query" : "this AND that OR thus",
"use_dis_max" : true
}
}
}
--------------------------------------------------
// CONSOLE
include::query-string-syntax.asciidoc[]