OpenSearch/docs/reference/search/suggesters/completion-suggest.asciidoc

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[[completion-suggester]]
==== Completion Suggester
NOTE: In order to understand the format of suggestions, please
read the <<search-suggesters>> page first. For more flexible
search-as-you-type searches that do not use suggesters, see the
<<search-as-you-type,`search_as_you_type` field type>>.
The `completion` suggester provides auto-complete/search-as-you-type
functionality. This is a navigational feature to guide users to
relevant results as they are typing, improving search precision.
It is not meant for spell correction or did-you-mean functionality
like the `term` or `phrase` suggesters.
Ideally, auto-complete functionality should be as fast as a user
types to provide instant feedback relevant to what a user has already
typed in. Hence, `completion` suggester is optimized for speed.
The suggester uses data structures that enable fast lookups,
but are costly to build and are stored in-memory.
[[completion-suggester-mapping]]
===== Mapping
To use this feature, specify a special mapping for this field,
which indexes the field values for fast completions.
[source,console]
--------------------------------------------------
PUT music
{
"mappings": {
"properties" : {
"suggest" : {
"type" : "completion"
},
"title" : {
"type": "keyword"
}
}
}
}
--------------------------------------------------
// TESTSETUP
Mapping supports the following parameters:
[horizontal]
`analyzer`::
The index analyzer to use, defaults to `simple`.
`search_analyzer`::
The search analyzer to use, defaults to value of `analyzer`.
`preserve_separators`::
Preserves the separators, defaults to `true`.
If disabled, you could find a field starting with `Foo Fighters`, if you
suggest for `foof`.
`preserve_position_increments`::
Enables position increments, defaults to `true`.
If disabled and using stopwords analyzer, you could get a
field starting with `The Beatles`, if you suggest for `b`. *Note*: You
could also achieve this by indexing two inputs, `Beatles` and
`The Beatles`, no need to change a simple analyzer, if you are able to
enrich your data.
`max_input_length`::
Limits the length of a single input, defaults to `50` UTF-16 code points.
This limit is only used at index time to reduce the total number of
characters per input string in order to prevent massive inputs from
bloating the underlying datastructure. Most use cases won't be influenced
by the default value since prefix completions seldom grow beyond prefixes longer
than a handful of characters.
[[indexing]]
===== Indexing
You index suggestions like any other field. A suggestion is made of an
`input` and an optional `weight` attribute. An `input` is the expected
text to be matched by a suggestion query and the `weight` determines how
the suggestions will be scored. Indexing a suggestion is as follows:
[source,console]
--------------------------------------------------
PUT music/_doc/1?refresh
{
"suggest" : {
"input": [ "Nevermind", "Nirvana" ],
"weight" : 34
}
}
--------------------------------------------------
// TEST
The following parameters are supported:
[horizontal]
`input`::
The input to store, this can be an array of strings or just
a string. This field is mandatory.
+
[NOTE]
====
This value cannot contain the following UTF-16 control characters:
* `\u0000` (null)
* `\u001f` (information separator one)
* `\u001e` (information separator two)
====
`weight`::
A positive integer or a string containing a positive integer,
which defines a weight and allows you to rank your suggestions.
This field is optional.
You can index multiple suggestions for a document as follows:
[source,console]
--------------------------------------------------
PUT music/_doc/1?refresh
{
"suggest" : [
{
"input": "Nevermind",
"weight" : 10
},
{
"input": "Nirvana",
"weight" : 3
}
]
}
--------------------------------------------------
// TEST[continued]
You can use the following shorthand form. Note that you can not specify
a weight with suggestion(s) in the shorthand form.
[source,console]
--------------------------------------------------
PUT music/_doc/1?refresh
{
"suggest" : [ "Nevermind", "Nirvana" ]
}
--------------------------------------------------
// TEST[continued]
[[querying]]
===== Querying
Suggesting works as usual, except that you have to specify the suggest
type as `completion`. Suggestions are near real-time, which means
new suggestions can be made visible by <<indices-refresh,refresh>> and
documents once deleted are never shown. This request:
[source,console]
--------------------------------------------------
POST music/_search?pretty
{
"suggest": {
"song-suggest" : {
"prefix" : "nir", <1>
"completion" : { <2>
"field" : "suggest" <3>
}
}
}
}
--------------------------------------------------
// TEST[continued]
<1> Prefix used to search for suggestions
<2> Type of suggestions
<3> Name of the field to search for suggestions in
returns this response:
[source,console-result]
--------------------------------------------------
{
"_shards" : {
"total" : 1,
"successful" : 1,
Add a shard filter search phase to pre-filter shards based on query rewriting (#25658) Today if we search across a large amount of shards we hit every shard. Yet, it's quite common to search across an index pattern for time based indices but filtering will exclude all results outside a certain time range ie. `now-3d`. While the search can potentially hit hundreds of shards the majority of the shards might yield 0 results since there is not document that is within this date range. Kibana for instance does this regularly but used `_field_stats` to optimize the indexes they need to query. Now with the deprecation of `_field_stats` and it's upcoming removal a single dashboard in kibana can potentially turn into searches hitting hundreds or thousands of shards and that can easily cause search rejections even though the most of the requests are very likely super cheap and only need a query rewriting to early terminate with 0 results. This change adds a pre-filter phase for searches that can, if the number of shards are higher than a the `pre_filter_shard_size` threshold (defaults to 128 shards), fan out to the shards and check if the query can potentially match any documents at all. While false positives are possible, a negative response means that no matches are possible. These requests are not subject to rejection and can greatly reduce the number of shards a request needs to hit. The approach here is preferable to the kibana approach with field stats since it correctly handles aliases and uses the correct threadpools to execute these requests. Further it's completely transparent to the user and improves scalability of elasticsearch in general on large clusters.
2017-07-12 16:19:20 -04:00
"skipped" : 0,
"failed" : 0
},
"hits": ...
"took": 2,
"timed_out": false,
"suggest": {
"song-suggest" : [ {
"text" : "nir",
"offset" : 0,
"length" : 3,
"options" : [ {
"text" : "Nirvana",
"_index": "music",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"suggest": ["Nevermind", "Nirvana"]
}
} ]
} ]
}
}
--------------------------------------------------
// TESTRESPONSE[s/"hits": .../"hits": "$body.hits",/]
// TESTRESPONSE[s/"took": 2,/"took": "$body.took",/]
IMPORTANT: `_source` meta-field must be enabled, which is the default
behavior, to enable returning `_source` with suggestions.
The configured weight for a suggestion is returned as `_score`. The
`text` field uses the `input` of your indexed suggestion. Suggestions
return the full document `_source` by default. The size of the `_source`
can impact performance due to disk fetch and network transport overhead.
To save some network overhead, filter out unnecessary fields from the `_source`
using <<request-body-search-source-filtering, source filtering>> to minimize
`_source` size. Note that the _suggest endpoint doesn't support source
filtering but using suggest on the `_search` endpoint does:
[source,console]
--------------------------------------------------
POST music/_search
{
"_source": "suggest", <1>
"suggest": {
"song-suggest" : {
"prefix" : "nir",
"completion" : {
"field" : "suggest", <2>
"size" : 5 <3>
}
}
}
}
--------------------------------------------------
// TEST[continued]
<1> Filter the source to return only the `suggest` field
<2> Name of the field to search for suggestions in
<3> Number of suggestions to return
Which should look like:
[source,console-result]
--------------------------------------------------
{
"took": 6,
"timed_out": false,
"_shards" : {
"total" : 1,
"successful" : 1,
Add a shard filter search phase to pre-filter shards based on query rewriting (#25658) Today if we search across a large amount of shards we hit every shard. Yet, it's quite common to search across an index pattern for time based indices but filtering will exclude all results outside a certain time range ie. `now-3d`. While the search can potentially hit hundreds of shards the majority of the shards might yield 0 results since there is not document that is within this date range. Kibana for instance does this regularly but used `_field_stats` to optimize the indexes they need to query. Now with the deprecation of `_field_stats` and it's upcoming removal a single dashboard in kibana can potentially turn into searches hitting hundreds or thousands of shards and that can easily cause search rejections even though the most of the requests are very likely super cheap and only need a query rewriting to early terminate with 0 results. This change adds a pre-filter phase for searches that can, if the number of shards are higher than a the `pre_filter_shard_size` threshold (defaults to 128 shards), fan out to the shards and check if the query can potentially match any documents at all. While false positives are possible, a negative response means that no matches are possible. These requests are not subject to rejection and can greatly reduce the number of shards a request needs to hit. The approach here is preferable to the kibana approach with field stats since it correctly handles aliases and uses the correct threadpools to execute these requests. Further it's completely transparent to the user and improves scalability of elasticsearch in general on large clusters.
2017-07-12 16:19:20 -04:00
"skipped" : 0,
"failed" : 0
},
"hits": {
"total" : {
"value": 0,
"relation": "eq"
},
"max_score" : null,
"hits" : []
},
"suggest": {
"song-suggest" : [ {
"text" : "nir",
"offset" : 0,
"length" : 3,
"options" : [ {
"text" : "Nirvana",
"_index": "music",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"suggest": ["Nevermind", "Nirvana"]
}
} ]
} ]
}
}
--------------------------------------------------
// TESTRESPONSE[s/"took": 6,/"took": $body.took,/]
The basic completion suggester query supports the following parameters:
[horizontal]
`field`:: The name of the field on which to run the query (required).
`size`:: The number of suggestions to return (defaults to `5`).
`skip_duplicates`:: Whether duplicate suggestions should be filtered out (defaults to `false`).
NOTE: The completion suggester considers all documents in the index.
See <<context-suggester>> for an explanation of how to query a subset of
documents instead.
NOTE: In case of completion queries spanning more than one shard, the suggest
is executed in two phases, where the last phase fetches the relevant documents
from shards, implying executing completion requests against a single shard is
more performant due to the document fetch overhead when the suggest spans
multiple shards. To get best performance for completions, it is recommended to
index completions into a single shard index. In case of high heap usage due to
shard size, it is still recommended to break index into multiple shards instead
of optimizing for completion performance.
[[skip_duplicates]]
===== Skip duplicate suggestions
Queries can return duplicate suggestions coming from different documents.
It is possible to modify this behavior by setting `skip_duplicates` to true.
When set, this option filters out documents with duplicate suggestions from the result.
[source,console]
--------------------------------------------------
POST music/_search?pretty
{
"suggest": {
"song-suggest" : {
"prefix" : "nor",
"completion" : {
"field" : "suggest",
"skip_duplicates": true
}
}
}
}
--------------------------------------------------
WARNING: When set to true, this option can slow down search because more suggestions
need to be visited to find the top N.
[[fuzzy]]
===== Fuzzy queries
The completion suggester also supports fuzzy queries -- this means
you can have a typo in your search and still get results back.
[source,console]
--------------------------------------------------
POST music/_search?pretty
{
"suggest": {
"song-suggest" : {
"prefix" : "nor",
"completion" : {
"field" : "suggest",
"fuzzy" : {
"fuzziness" : 2
}
}
}
}
}
--------------------------------------------------
Suggestions that share the longest prefix to the query `prefix` will
be scored higher.
The fuzzy query can take specific fuzzy parameters.
The following parameters are supported:
[horizontal]
`fuzziness`::
The fuzziness factor, defaults to `AUTO`.
See <<fuzziness>> for allowed settings.
`transpositions`::
if set to `true`, transpositions are counted
as one change instead of two, defaults to `true`
`min_length`::
Minimum length of the input before fuzzy
suggestions are returned, defaults `3`
`prefix_length`::
Minimum length of the input, which is not
checked for fuzzy alternatives, defaults to `1`
`unicode_aware`::
If `true`, all measurements (like fuzzy edit
distance, transpositions, and lengths) are
measured in Unicode code points instead of
in bytes. This is slightly slower than raw
bytes, so it is set to `false` by default.
NOTE: If you want to stick with the default values, but
still use fuzzy, you can either use `fuzzy: {}`
or `fuzzy: true`.
[[regex]]
===== Regex queries
The completion suggester also supports regex queries meaning
you can express a prefix as a regular expression
[source,console]
--------------------------------------------------
POST music/_search?pretty
{
"suggest": {
"song-suggest" : {
"regex" : "n[ever|i]r",
"completion" : {
"field" : "suggest"
}
}
}
}
--------------------------------------------------
The regex query can take specific regex parameters.
The following parameters are supported:
[horizontal]
`flags`::
Possible flags are `ALL` (default), `ANYSTRING`, `COMPLEMENT`,
`EMPTY`, `INTERSECTION`, `INTERVAL`, or `NONE`. See <<query-dsl-regexp-query, regexp-syntax>>
for their meaning
`max_determinized_states`::
Regular expressions are dangerous because it's easy to accidentally
create an innocuous looking one that requires an exponential number of
internal determinized automaton states (and corresponding RAM and CPU)
for Lucene to execute. Lucene prevents these using the
`max_determinized_states` setting (defaults to 10000). You can raise
this limit to allow more complex regular expressions to execute.