elasticsearch/docs/reference/elasticsearch/mapping-reference/rank-feature.md
Craig Taverner 94cad286bc
Restructure query-languages docs files for clarity (#124797)
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.
2025-03-17 17:58:58 +01:00

1.9 KiB

navigation_title mapped_pages
Rank feature
https://www.elastic.co/guide/en/elasticsearch/reference/current/rank-feature.html

Rank feature field type [rank-feature]

A rank_feature field can index numbers so that they can later be used to boost documents in queries with a rank_feature query.

PUT my-index-000001
{
  "mappings": {
    "properties": {
      "pagerank": {
        "type": "rank_feature" <1>
      },
      "url_length": {
        "type": "rank_feature",
        "positive_score_impact": false <2>
      }
    }
  }
}

PUT my-index-000001/_doc/1
{
  "pagerank": 8,
  "url_length": 22
}

GET my-index-000001/_search
{
  "query": {
    "rank_feature": {
      "field": "pagerank"
    }
  }
}
  1. Rank feature fields must use the rank_feature field type
  2. Rank features that correlate negatively with the score need to declare it

::::{note} rank_feature fields only support single-valued fields and strictly positive values. Multi-valued fields and negative values will be rejected. ::::

::::{note} rank_feature fields do not support querying, sorting or aggregating. They may only be used within rank_feature queries. ::::

::::{note} rank_feature fields only preserve 9 significant bits for the precision, which translates to a relative error of about 0.4%. ::::

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 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.