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