kibana/docs/discover/kuery.asciidoc
2018-09-25 12:46:00 -04:00

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[[kuery-query]]
=== Kibana Query Language Enhancements
experimental[This functionality is experimental and may be changed or removed completely in a future release.]
[NOTE]
============
In 6.0 we introduced an experimental query language called Kuery. We've taken what we learned from that experiment
and applied it to the standard Kibana query language. As a result, Kuery is no longer available as a standalone
option. Saved searches using Kuery will automatically be opted in to using the language enhancements described on
this page. However, some breaking changes have been made to the query syntax, so read on for the full details on
what's new.
============
Starting in 6.3, you can choose to opt-in to a number of exciting experimental query language enhancements under the
options menu in the query bar. Currently, opting in will enable scripted field support and a simplified, easier to
use syntax. If you have a Basic license or above, autocomplete functionality will also be enabled. We're hard at
work building even more features for you to try out. Take these features for a spin and let us know what you think!
==== New Simplified Syntax
If you're familiar with Kibana's old lucene query syntax, you should feel right at home with the new syntax. The basics
stay the same, we've simply refined things to make the query language easier to use. Read about the changes below.
`response:200` will match documents where the response field matches the value 200.
Quotes around a search term will initiate a phrase search. For example, `message:"Quick brown fox"` will search
for the phrase "quick brown fox" in the message field. Without the quotes, your query will get broken down into tokens via
the message field's configured analyzer and will match documents that contain those tokens, regardless of the order in which
they appear. This means documents with "quick brown fox" will match, but so will "quick fox brown". Remember to use quotes if you want
to search for a phrase.
The query parser will no longer split on whitespace. Multiple search terms must be separated by explicit
boolean operators. Note that boolean operators are not case sensitive.
`response:200 extension:php` in lucene would become `response:200 and extension:php`.
This will match documents where response matches 200 and extension matches php.
We can make terms optional by using `or`.
`response:200 or extension:php` will match documents where response matches 200, extension matches php, or both.
By default, `and` has a higher precedence than `or`.
`response:200 and extension:php or extension:css` will match documents where response is 200 and extension is php OR documents where extension is css and response is anything.
We can override the default precedence with grouping.
`response:200 and (extension:php or extension:css)` will match documents where response is 200 and extension is either php or css.
A shorthand exists that allows us to easily search a single field for multiple values.
`response:(200 or 404)` searches for docs where the `response` field matches 200 or 404. We can also search for docs
with multi-value fields that contain a list of terms, for example: `tags:(success and info and security)`
Terms can be inverted by prefixing them with `not`.
`not response:200` will match all documents where response is not 200.
Entire groups can also be inverted.
`response:200 and not (extension:php or extension:css)`
Ranges are similar to lucene with a small syntactical difference.
Instead of `bytes:>1000`, we omit the colon: `bytes > 1000`.
`>, >=, <, <=` are all valid range operators.
Exist queries are simple and do not require a special operator. `response:*` will find all docs where the response
field exists.
Wildcard queries are available. `machine.os:win*` would match docs where the machine.os field starts with "win", which
would match values like "windows 7" and "windows 10".
Wildcards also allow us to search multiple fields at once. This can come in handy when you have both `text` and `keyword`
versions of a field. Let's say we have `machine.os` and `machine.os.keyword` fields and we want to check both for the term
"windows 10". We can do it like this: `machine.os*:windows 10".
[NOTE]
============
Terms without fields will be matched against the default field in your index settings. If a default field is not
set these terms will be matched against all fields. For example, a query for `response:200` will search for the value 200
in the response field, but a query for just `200` will search for 200 across all fields in your index.
============