OpenSearch/docs/reference/search.asciidoc

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[[search]]
= Search APIs
[partintro]
--
Most search APIs are <<search-multi-index-type,multi-index&#44; multi-type>>, with the
exception of the <<search-explain>> endpoints.
[float]
[[search-routing]]
== Routing
When executing a search, Elasticsearch will pick the "best" copy of the data
based on the <<search-adaptive-replica,adaptive replica selection>> formula.
Which shards will be searched on can also be controlled by providing the
`routing` parameter. For example, when indexing tweets, the routing value can be
the user name:
[source,js]
--------------------------------------------------
POST /twitter/tweet?routing=kimchy
{
"user" : "kimchy",
"postDate" : "2009-11-15T14:12:12",
"message" : "trying out Elasticsearch"
}
--------------------------------------------------
// CONSOLE
In such a case, if we want to search only on the tweets for a specific
user, we can specify it as the routing, resulting in the search hitting
only the relevant shard:
[source,js]
--------------------------------------------------
POST /twitter/_search?routing=kimchy
{
"query": {
"bool" : {
"must" : {
"query_string" : {
"query" : "some query string here"
}
},
"filter" : {
"term" : { "user" : "kimchy" }
}
}
}
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
The routing parameter can be multi valued represented as a comma
separated string. This will result in hitting the relevant shards where
the routing values match to.
[float]
[[search-adaptive-replica]]
== Adaptive Replica Selection
By default, Elasticsearch will use what is called adaptive replica selection.
This allows the coordinating node to send the request to the copy deemed "best"
based on a number of criteria:
- Response time of past requests between the coordinating node and the node
containing the copy of the data
- Time past search requests took to execute on the node containing the data
- The queue size of the search threadpool on the node containing the data
This can be turned off by changing the dynamic cluster setting
`cluster.routing.use_adaptive_replica_selection` from `true` to `false`:
[source,js]
--------------------------------------------------
PUT /_cluster/settings
{
"transient": {
"cluster.routing.use_adaptive_replica_selection": false
}
}
--------------------------------------------------
// CONSOLE
If adaptive replica selection is turned off, searches are sent to the
index/indices shards in a round robin fashion between all copies of the data
(primaries and replicas).
[float]
[[stats-groups]]
== Stats Groups
A search can be associated with stats groups, which maintains a
statistics aggregation per group. It can later be retrieved using the
<<indices-stats,indices stats>> API
specifically. For example, here is a search body request that associate
the request with two different groups:
[source,js]
--------------------------------------------------
POST /_search
{
"query" : {
"match_all" : {}
},
"stats" : ["group1", "group2"]
}
--------------------------------------------------
// CONSOLE
// TEST[setup:twitter]
[float]
[[global-search-timeout]]
== Global Search Timeout
Individual searches can have a timeout as part of the
<<search-request-body>>. Since search requests can originate from many
sources, Elasticsearch has a dynamic cluster-level setting for a global
search timeout that applies to all search requests that do not set a
timeout in the request body. These requests will be cancelled after
the specified time using the mechanism described in the following section on
<<global-search-cancellation>>. Therefore the same caveats about timeout
responsiveness apply.
The setting key is `search.default_search_timeout` and can be set using the
<<cluster-update-settings>> endpoints. The default value is no global timeout.
Setting this value to `-1` resets the global search timeout to no timeout.
[float]
[[global-search-cancellation]]
== Search Cancellation
Searches can be cancelled using standard <<task-cancellation,task cancellation>>
mechanism. By default, a running search only checks if it is cancelled or
not on segment boundaries, therefore the cancellation can be delayed by large
segments. The search cancellation responsiveness can be improved by setting
the dynamic cluster-level setting `search.low_level_cancellation` to `true`.
However, it comes with an additional overhead of more frequent cancellation
checks that can be noticeable on large fast running search queries. Changing this
setting only affects the searches that start after the change is made.
[float]
[[search-concurrency-and-parallelism]]
== Search concurrency and parallelism
By default Elasticsearch doesn't reject any search requests based on the number
of shards the request hits. While Elasticsearch will optimize the search
execution on the coordinating node a large number of shards can have a
significant impact CPU and memory wise. It is usually a better idea to organize
data in such a way that there are fewer larger shards. In case you would like to
configure a soft limit, you can update the `action.search.shard_count.limit`
cluster setting in order to reject search requests that hit too many shards.
The request parameter `max_concurrent_shard_requests` can be used to control the
maximum number of concurrent shard requests the search API will execute for the
request. This parameter should be used to protect a single request from
overloading a cluster (e.g., a default request will hit all indices in a cluster
which could cause shard request rejections if the number of shards per node is
high). This default is based on the number of data nodes in the cluster but at
most `256`.
--
include::search/search.asciidoc[]
include::search/uri-request.asciidoc[]
include::search/request-body.asciidoc[]
include::search/search-template.asciidoc[]
include::search/search-shards.asciidoc[]
include::search/suggesters.asciidoc[]
include::search/multi-search.asciidoc[]
include::search/count.asciidoc[]
include::search/validate.asciidoc[]
include::search/explain.asciidoc[]
include::search/profile.asciidoc[]
include::search/field-caps.asciidoc[]
include::search/rank-eval.asciidoc[]