82 lines
3.6 KiB
Plaintext
82 lines
3.6 KiB
Plaintext
[[request-body-search-search-after]]
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=== Search After
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Pagination of results can be done by using the `from` and `size` but the cost becomes prohibitive when the deep pagination is reached.
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The `index.max_result_window` which defaults to 10,000 is a safeguard, search requests take heap memory and time proportional to `from + size`.
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The <<search-request-scroll,Scroll>> api is recommended for efficient deep scrolling but scroll contexts are costly and it is not
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recommended to use it for real time user requests.
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The `search_after` parameter circumvents this problem by providing a live cursor.
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The idea is to use the results from the previous page to help the retrieval of the next page.
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Suppose that the query to retrieve the first page looks like this:
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[source,js]
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--------------------------------------------------
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GET twitter/_search
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{
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"size": 10,
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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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"sort": [
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{"date": "asc"},
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{"tie_breaker_id": "asc"} <1>
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]
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[setup:twitter]
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// TEST[s/"tie_breaker_id": "asc"/"tie_breaker_id": {"unmapped_type": "keyword"}/]
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<1> A copy of the `_id` field with `doc_values` enabled
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[IMPORTANT]
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A field with one unique value per document should be used as the tiebreaker
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of the sort specification. Otherwise the sort order for documents that have
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the same sort values would be undefined and could lead to missing or duplicate
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results. The <<mapping-id-field,`_id` field>> has a unique value per document
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but it is not recommended to use it as a tiebreaker directly.
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Beware that `search_after` looks for the first document which fully or partially
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matches tiebreaker's provided value. Therefore if a document has a tiebreaker value of
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`"654323"` and you `search_after` for `"654"` it would still match that document
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and return results found after it.
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<<doc-values,doc value>> are disabled on this field so sorting on it requires
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to load a lot of data in memory. Instead it is advised to duplicate (client side
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or with a <<ingest-processors,set ingest processor>>) the content
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of the <<mapping-id-field,`_id` field>> in another field that has
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<<doc-values,doc value>> enabled and to use this new field as the tiebreaker
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for the sort.
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The result from the above request includes an array of `sort values` for each document.
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These `sort values` can be used in conjunction with the `search_after` parameter to start returning results "after" any
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document in the result list.
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For instance we can use the `sort values` of the last document and pass it to `search_after` to retrieve the next page of results:
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[source,js]
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--------------------------------------------------
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GET twitter/_search
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{
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"size": 10,
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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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"search_after": [1463538857, "654323"],
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"sort": [
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{"date": "asc"},
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{"tie_breaker_id": "asc"}
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]
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[setup:twitter]
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// TEST[s/"tie_breaker_id": "asc"/"tie_breaker_id": {"unmapped_type": "keyword"}/]
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NOTE: The parameter `from` must be set to 0 (or -1) when `search_after` is used.
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`search_after` is not a solution to jump freely to a random page but rather to scroll many queries in parallel.
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It is very similar to the `scroll` API but unlike it, the `search_after` parameter is stateless, it is always resolved against the latest
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version of the searcher. For this reason the sort order may change during a walk depending on the updates and deletes of your index.
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