2013-08-28 19:24:34 -04:00
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[[search-request-rescore]]
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=== Rescoring
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Rescoring can help to improve precision by reordering just the top (eg
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100 - 500) documents returned by the
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<<search-request-query,`query`>> and
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2013-12-16 12:07:33 -05:00
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<<search-request-post-filter,`post_filter`>> phases, using a
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2013-08-28 19:24:34 -04:00
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secondary (usually more costly) algorithm, instead of applying the
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costly algorithm to all documents in the index.
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A `rescore` request is executed on each shard before it returns its
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results to be sorted by the node handling the overall search request.
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Currently the rescore API has only one implementation: the query
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rescorer, which uses a query to tweak the scoring. In the future,
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alternative rescorers may be made available, for example, a pair-wise rescorer.
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2014-10-18 05:25:50 -04:00
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NOTE: when exposing pagination to your users, you should not change
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`window_size` as you step through each page (by passing different
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`from` values) since that can alter the top hits causing results to
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confusingly shift as the user steps through pages.
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2013-08-28 19:24:34 -04:00
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==== Query rescorer
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The query rescorer executes a second query only on the Top-K results
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returned by the <<search-request-query,`query`>> and
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2013-12-16 12:07:33 -05:00
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<<search-request-post-filter,`post_filter`>> phases. The
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2013-08-28 19:24:34 -04:00
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number of docs which will be examined on each shard can be controlled by
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the `window_size` parameter, which defaults to
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<<search-request-from-size,`from` and `size`>>.
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2014-01-23 10:22:39 -05:00
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By default the scores from the original query and the rescore query are
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combined linearly to produce the final `_score` for each document. The
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relative importance of the original query and of the rescore query can
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be controlled with the `query_weight` and `rescore_query_weight`
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respectively. Both default to `1`.
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For example:
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[source,js]
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--------------------------------------------------
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curl -s -XPOST 'localhost:9200/_search' -d '{
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"query" : {
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"match" : {
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"field1" : {
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2013-10-05 11:18:15 -04:00
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"operator" : "or",
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"query" : "the quick brown",
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"type" : "boolean"
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}
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}
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},
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"rescore" : {
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"window_size" : 50,
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"query" : {
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"rescore_query" : {
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"match" : {
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"field1" : {
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"query" : "the quick brown",
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"type" : "phrase",
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"slop" : 2
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}
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}
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},
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"query_weight" : 0.7,
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"rescore_query_weight" : 1.2
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}
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}
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}
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'
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--------------------------------------------------
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2015-05-05 04:03:15 -04:00
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The way the scores are combined can be controlled with the `score_mode`:
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[cols="<,<",options="header",]
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|=======================================================================
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|Score Mode |Description
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|`total` |Add the original score and the rescore query score. The default.
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|`multiply` |Multiply the original score by the rescore query score. Useful
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for <<query-dsl-function-score-query,`function query`>> rescores.
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|`avg` |Average the original score and the rescore query score.
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|`max` |Take the max of original score and the rescore query score.
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|`min` |Take the min of the original score and the rescore query score.
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|=======================================================================
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2014-01-15 17:58:22 -05:00
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==== Multiple Rescores
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It is also possible to execute multiple rescores in sequence:
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[source,js]
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--------------------------------------------------
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curl -s -XPOST 'localhost:9200/_search' -d '{
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"query" : {
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"match" : {
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"field1" : {
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"operator" : "or",
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"query" : "the quick brown",
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"type" : "boolean"
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}
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}
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},
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"rescore" : [ {
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"window_size" : 100,
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"query" : {
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"rescore_query" : {
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"match" : {
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"field1" : {
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"query" : "the quick brown",
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"type" : "phrase",
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"slop" : 2
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}
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}
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},
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"query_weight" : 0.7,
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"rescore_query_weight" : 1.2
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}
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}, {
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"window_size" : 10,
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"query" : {
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"score_mode": "multiply",
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"rescore_query" : {
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"function_score" : {
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"script_score": {
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2016-06-27 09:55:16 -04:00
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"script": {
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"lang": "painless",
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"inline": "Math.log10(doc['numeric'].value + 2)"
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}
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2014-01-15 17:58:22 -05:00
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}
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}
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}
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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 first one gets the results of the query then the second one gets the
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results of the first, etc. The second rescore will "see" the sorting done
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by the first rescore so it is possible to use a large window on the first
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rescore to pull documents into a smaller window for the second rescore.
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