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94cad286bc
In a few previous PR's we restructured the ES|QL docs to make it possible to generate them dynamically. This PR just moves a few files around to make the query languages docs easier to work with, and a little more organized like the ES|QL docs. A bit part of this was setting up redirects to the new locations, so other repo's could correctly link to the elasticsearch docs.
64 lines
1.9 KiB
Markdown
64 lines
1.9 KiB
Markdown
---
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navigation_title: "Rank feature"
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mapped_pages:
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- https://www.elastic.co/guide/en/elasticsearch/reference/current/rank-feature.html
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---
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# Rank feature field type [rank-feature]
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A `rank_feature` field can index numbers so that they can later be used to boost documents in queries with a [`rank_feature`](/reference/query-languages/query-dsl/query-dsl-rank-feature-query.md) query.
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```console
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PUT my-index-000001
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{
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"mappings": {
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"properties": {
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"pagerank": {
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"type": "rank_feature" <1>
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},
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"url_length": {
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"type": "rank_feature",
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"positive_score_impact": false <2>
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}
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}
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}
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}
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PUT my-index-000001/_doc/1
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{
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"pagerank": 8,
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"url_length": 22
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}
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GET my-index-000001/_search
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{
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"query": {
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"rank_feature": {
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"field": "pagerank"
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}
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}
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}
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```
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1. Rank feature fields must use the `rank_feature` field type
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2. Rank features that correlate negatively with the score need to declare it
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::::{note}
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`rank_feature` fields only support single-valued fields and strictly positive values. Multi-valued fields and negative values will be rejected.
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::::
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::::{note}
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`rank_feature` fields do not support querying, sorting or aggregating. They may only be used within [`rank_feature`](/reference/query-languages/query-dsl/query-dsl-rank-feature-query.md) queries.
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::::
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::::{note}
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`rank_feature` fields only preserve 9 significant bits for the precision, which translates to a relative error of about 0.4%.
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::::
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Rank features that correlate negatively with the score should set `positive_score_impact` to `false` (defaults to `true`). This will be used by the [`rank_feature`](/reference/query-languages/query-dsl/query-dsl-rank-feature-query.md) query to modify the scoring formula in such a way that the score decreases with the value of the feature instead of increasing. For instance in web search, the url length is a commonly used feature which correlates negatively with scores.
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