223 lines
8.2 KiB
Plaintext
223 lines
8.2 KiB
Plaintext
[[search-request-scroll]]
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=== Scroll
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While a `search` request returns a single ``page'' of results, the `scroll`
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API can be used to retrieve large numbers of results (or even all results)
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from a single search request, in much the same way as you would use a cursor
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on a traditional database.
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Scrolling is not intended for real time user requests, but rather for
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processing large amounts of data, e.g. in order to reindex the contents of one
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index into a new index with a different configuration.
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.Client support for scrolling and reindexing
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*********************************************
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Some of the officially supported clients provide helpers to assist with
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scrolled searches and reindexing of documents from one index to another:
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Perl::
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See https://metacpan.org/pod/Search::Elasticsearch::Bulk[Search::Elasticsearch::Bulk]
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and https://metacpan.org/pod/Search::Elasticsearch::Scroll[Search::Elasticsearch::Scroll]
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Python::
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See http://elasticsearch-py.readthedocs.org/en/master/helpers.html[elasticsearch.helpers.*]
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*********************************************
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NOTE: The results that are returned from a scroll request reflect the state of
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the index at the time that the initial `search` request was made, like a
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snapshot in time. Subsequent changes to documents (index, update or delete)
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will only affect later search requests.
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In order to use scrolling, the initial search request should specify the
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`scroll` parameter in the query string, which tells Elasticsearch how long it
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should keep the ``search context'' alive (see <<scroll-search-context>>), eg `?scroll=1m`.
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[source,js]
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--------------------------------------------------
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curl -XGET 'localhost:9200/twitter/tweet/_search?scroll=1m' -d '
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{
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"query": {
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"match" : {
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"title" : "elasticsearch"
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}
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}
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}
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'
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--------------------------------------------------
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The result from the above request includes a `_scroll_id`, which should
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be passed to the `scroll` API in order to retrieve the next batch of
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results.
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[source,js]
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--------------------------------------------------
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curl -XGET <1> 'localhost:9200/_search/scroll' <2> -d'
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{
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"scroll" : "1m", <3>
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"scroll_id" : "c2Nhbjs2OzM0NDg1ODpzRlBLc0FXNlNyNm5JWUc1" <4>
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}
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'
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--------------------------------------------------
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coming[2.0.0-beta1, body based parameters were added in 2.0.0]
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<1> `GET` or `POST` can be used.
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<2> The URL should not include the `index` or `type` name -- these
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are specified in the original `search` request instead.
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<3> The `scroll` parameter tells Elasticsearch to keep the search context open
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for another `1m`.
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<4> The `scroll_id` parameter
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Each call to the `scroll` API returns the next batch of results until there
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are no more results left to return, ie the `hits` array is empty.
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For backwards compatibility, `scroll_id` and `scroll` can be passed in the query string.
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And the `scroll_id` can be passed in the request body
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[source,js]
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--------------------------------------------------
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curl -XGET 'localhost:9200/_search/scroll?scroll=1m' -d 'c2Nhbjs2OzM0NDg1ODpzRlBLc0FXNlNyNm5JWUc1'
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--------------------------------------------------
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IMPORTANT: The initial search request and each subsequent scroll request
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returns a new `_scroll_id` -- only the most recent `_scroll_id` should be
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used.
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NOTE: If the request specifies aggregations, only the initial search response
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will contain the aggregations results.
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[[scroll-scan]]
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==== Efficient scrolling with Scroll-Scan
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Deep pagination with <<search-request-from-size,`from` and `size`>> -- e.g.
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`?size=10&from=10000` -- is very inefficient as (in this example) 100,000
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sorted results have to be retrieved from each shard and resorted in order to
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return just 10 results. This process has to be repeated for every page
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requested.
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The `scroll` API keeps track of which results have already been returned and
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so is able to return sorted results more efficiently than with deep
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pagination. However, sorting results (which happens by default) still has a
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cost.
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Normally, you just want to retrieve all results and the order doesn't matter.
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Scrolling can be combined with the <<scan,`scan`>> search type to disable
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any scoring or sorting and to return results in the most efficient way
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possible. All that is needed is to add `search_type=scan` to the query string
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of the initial search request:
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[source,js]
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--------------------------------------------------
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curl 'localhost:9200/twitter/tweet/_search?scroll=1m&search_type=scan' <1> -d '
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{
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"query": {
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"match" : {
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"title" : "elasticsearch"
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}
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}
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}
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'
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--------------------------------------------------
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<1> Setting `search_type` to `scan` disables sorting and makes scrolling
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very efficient.
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A scanning scroll request differs from a standard scroll request in four
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ways:
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* No score is calculated and sorting is disabled. Results are returned in
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the order they appear in the index.
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* Aggregations are not supported.
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* The response of the initial `search` request will not contain any results in
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the `hits` array. The first results will be returned by the first `scroll`
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request.
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* The <<search-request-from-size,`size` parameter>> controls the number of
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results *per shard*, not per request, so a `size` of `10` which hits 5
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shards will return a maximum of 50 results per `scroll` request.
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If you want the scoring to happen, even without sorting on it, set the
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`track_scores` parameter to `true`.
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[[scroll-search-context]]
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==== Keeping the search context alive
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The `scroll` parameter (passed to the `search` request and to every `scroll`
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request) tells Elasticsearch how long it should keep the search context alive.
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Its value (e.g. `1m`, see <<time-units>>) does not need to be long enough to
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process all data -- it just needs to be long enough to process the previous
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batch of results. Each `scroll` request (with the `scroll` parameter) sets a
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new expiry time.
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Normally, the <<index-modules-merge,background merge process>> optimizes the
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index by merging together smaller segments to create new bigger segments, at
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which time the smaller segments are deleted. This process continues during
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scrolling, but an open search context prevents the old segments from being
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deleted while they are still in use. This is how Elasticsearch is able to
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return the results of the initial search request, regardless of subsequent
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changes to documents.
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TIP: Keeping older segments alive means that more file handles are needed.
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Ensure that you have configured your nodes to have ample free file handles.
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See <<file-descriptors>>.
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You can check how many search contexts are open with the
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<<cluster-nodes-stats,nodes stats API>>:
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[source,js]
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---------------------------------------
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curl -XGET localhost:9200/_nodes/stats/indices/search?pretty
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---------------------------------------
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==== Clear scroll API
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Search context are automatically removed when the `scroll` timeout has been
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exceeded. However keeping scrolls open has a cost, as discussed in the
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<<scroll-search-context,previous section>> so scrolls should be explicitly
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cleared as soon as the scroll is not being used anymore using the
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`clear-scroll` API:
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[source,js]
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---------------------------------------
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curl -XDELETE localhost:9200/_search/scroll -d '
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{
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"scroll_id" : ["c2Nhbjs2OzM0NDg1ODpzRlBLc0FXNlNyNm5JWUc1"]
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}'
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---------------------------------------
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coming[2.0.0-beta1, Body based parameters were added in 2.0.0]
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Multiple scroll IDs can be passed as array:
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[source,js]
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---------------------------------------
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curl -XDELETE localhost:9200/_search/scroll -d '
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{
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"scroll_id" : ["c2Nhbjs2OzM0NDg1ODpzRlBLc0FXNlNyNm5JWUc1", "aGVuRmV0Y2g7NTsxOnkxaDZ"]
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}'
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---------------------------------------
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coming[2.0.0-beta1, Body based parameters were added in 2.0.0]
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All search contexts can be cleared with the `_all` parameter:
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[source,js]
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---------------------------------------
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curl -XDELETE localhost:9200/_search/scroll/_all
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---------------------------------------
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The `scroll_id` can also be passed as a query string parameter or in the request body.
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Multiple scroll IDs can be passed as comma separated values:
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[source,js]
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---------------------------------------
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curl -XDELETE localhost:9200/_search/scroll \
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-d 'c2Nhbjs2OzM0NDg1ODpzRlBLc0FXNlNyNm5JWUc1,aGVuRmV0Y2g7NTsxOnkxaDZ'
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---------------------------------------
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