WARNING: Version 2.1 of Elasticsearch has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
Rescoring
editRescoring
editRescoring can help to improve precision by reordering just the top (eg
100 - 500) documents returned by the
query and
post_filter phases, using a
secondary (usually more costly) algorithm, instead of applying the
costly algorithm to all documents in the index.
A rescore request is executed on each shard before it returns its
results to be sorted by the node handling the overall search request.
Currently the rescore API has only one implementation: the query rescorer, which uses a query to tweak the scoring. In the future, alternative rescorers may be made available, for example, a pair-wise rescorer.
the rescore phase is not executed when
search_type is set
to scan or count.
when exposing pagination to your users, you should not change
window_size as you step through each page (by passing different
from values) since that can alter the top hits causing results to
confusingly shift as the user steps through pages.
Query rescorer
editThe query rescorer executes a second query only on the Top-K results
returned by the query and
post_filter phases. The
number of docs which will be examined on each shard can be controlled by
the window_size parameter, which defaults to
from and size.
By default the scores from the original query and the rescore query are
combined linearly to produce the final _score for each document. The
relative importance of the original query and of the rescore query can
be controlled with the query_weight and rescore_query_weight
respectively. Both default to 1.
For example:
curl -s -XPOST 'localhost:9200/_search' -d '{
"query" : {
"match" : {
"field1" : {
"operator" : "or",
"query" : "the quick brown",
"type" : "boolean"
}
}
},
"rescore" : {
"window_size" : 50,
"query" : {
"rescore_query" : {
"match" : {
"field1" : {
"query" : "the quick brown",
"type" : "phrase",
"slop" : 2
}
}
},
"query_weight" : 0.7,
"rescore_query_weight" : 1.2
}
}
}
'
The way the scores are combined can be controlled with the score_mode:
| Score Mode | Description |
|---|---|
|
Add the original score and the rescore query score. The default. |
|
Multiply the original score by the rescore query score. Useful
for |
|
Average the original score and the rescore query score. |
|
Take the max of original score and the rescore query score. |
|
Take the min of the original score and the rescore query score. |
Multiple Rescores
editIt is also possible to execute multiple rescores in sequence:
curl -s -XPOST 'localhost:9200/_search' -d '{
"query" : {
"match" : {
"field1" : {
"operator" : "or",
"query" : "the quick brown",
"type" : "boolean"
}
}
},
"rescore" : [ {
"window_size" : 100,
"query" : {
"rescore_query" : {
"match" : {
"field1" : {
"query" : "the quick brown",
"type" : "phrase",
"slop" : 2
}
}
},
"query_weight" : 0.7,
"rescore_query_weight" : 1.2
}
}, {
"window_size" : 10,
"query" : {
"score_mode": "multiply",
"rescore_query" : {
"function_score" : {
"script_score": {
"script": "log10(doc['numeric'].value + 2)"
}
}
}
}
} ]
}
'
The first one gets the results of the query then the second one gets the results of the first, etc. The second rescore will "see" the sorting done by the first rescore so it is possible to use a large window on the first rescore to pull documents into a smaller window for the second rescore.