**IMPORTANT**: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.

Boosts the relevance score of documents based on the
numeric value of a `rank_feature`

or
`rank_features`

field.

The `rank_feature`

query is typically used in the `should`

clause of a
`bool`

query so its relevance scores are added to other
scores from the `bool`

query.

Unlike the `function_score`

query or other
ways to change relevance scores, the
`rank_feature`

query efficiently skips non-competitive hits when the
`track_total_hits`

parameter is **not** `true`

. This can
dramatically improve query speed.

To calculate relevance scores based on rank feature fields, the `rank_feature`

query supports the following mathematical functions:

If you don’t know where to start, we recommend using the `saturation`

function.
If no function is provided, the `rank_feature`

query uses the `saturation`

function by default.

To use the `rank_feature`

query, your index must include a
`rank_feature`

or `rank_features`

field
mapping. To see how you can set up an index for the `rank_feature`

query, try
the following example.

Create a `test`

index with the following field mappings:

`pagerank`

, a`rank_feature`

field which measures the importance of a website`url_length`

, a`rank_feature`

field which contains the length of the website’s URL. For this example, a long URL correlates negatively to relevance, indicated by a`positive_score_impact`

value of`false`

.`topics`

, a`rank_features`

field which contains a list of topics and a measure of how well each document is connected to this topic

PUT /test { "mappings": { "properties": { "pagerank": { "type": "rank_feature" }, "url_length": { "type": "rank_feature", "positive_score_impact": false }, "topics": { "type": "rank_features" } } } }

Index several documents to the `test`

index.

PUT /test/_doc/1?refresh { "url": "http://en.wikipedia.org/wiki/2016_Summer_Olympics", "content": "Rio 2016", "pagerank": 50.3, "url_length": 42, "topics": { "sports": 50, "brazil": 30 } } PUT /test/_doc/2?refresh { "url": "http://en.wikipedia.org/wiki/2016_Brazilian_Grand_Prix", "content": "Formula One motor race held on 13 November 2016", "pagerank": 50.3, "url_length": 47, "topics": { "sports": 35, "formula one": 65, "brazil": 20 } } PUT /test/_doc/3?refresh { "url": "http://en.wikipedia.org/wiki/Deadpool_(film)", "content": "Deadpool is a 2016 American superhero film", "pagerank": 50.3, "url_length": 37, "topics": { "movies": 60, "super hero": 65 } }

The following query searches for `2016`

and boosts relevance scores based or
`pagerank`

, `url_length`

, and the `sports`

topic.

GET /test/_search { "query": { "bool": { "must": [ { "match": { "content": "2016" } } ], "should": [ { "rank_feature": { "field": "pagerank" } }, { "rank_feature": { "field": "url_length", "boost": 0.1 } }, { "rank_feature": { "field": "topics.sports", "boost": 0.4 } } ] } } }

`field`

- (Required, string)
`rank_feature`

or`rank_features`

field used to boost relevance scores. `boost`

(Optional, float) Floating point number used to decrease or increase relevance scores. Defaults to

`1.0`

.Boost values are relative to the default value of

`1.0`

. A boost value between`0`

and`1.0`

decreases the relevance score. A value greater than`1.0`

increases the relevance score.`saturation`

(Optional, function object) Saturation function used to boost relevance scores based on the value of the rank feature

`field`

. If no function is provided, the`rank_feature`

query defaults to the`saturation`

function. See Saturation for more information.Only one function

`saturation`

,`log`

, or`sigmoid`

can be provided.`log`

(Optional, function object) Logarithmic function used to boost relevance scores based on the value of the rank feature

`field`

. See Logarithm for more information.Only one function

`saturation`

,`log`

, or`sigmoid`

can be provided.`sigmoid`

(Optional, function object) Sigmoid function used to boost relevance scores based on the value of the rank feature

`field`

. See Sigmoid for more information.Only one function

`saturation`

,`log`

, or`sigmoid`

can be provided.

The `saturation`

function gives a score equal to `S / (S + pivot)`

, where `S`

is
the value of the rank feature field and `pivot`

is a configurable pivot value so
that the result will be less than `0.5`

if `S`

is less than pivot and greater
than `0.5`

otherwise. Scores are always `(0,1)`

.

If the rank feature has a negative score impact then the function will be
computed as `pivot / (S + pivot)`

, which decreases when `S`

increases.

GET /test/_search { "query": { "rank_feature": { "field": "pagerank", "saturation": { "pivot": 8 } } } }

If a `pivot`

value is not provided, Elasticsearch computes a default value equal to the
approximate geometric mean of all rank feature values in the index. We recommend
using this default value if you haven’t had the opportunity to train a good
pivot value.

GET /test/_search { "query": { "rank_feature": { "field": "pagerank", "saturation": {} } } }

The `log`

function gives a score equal to `log(scaling_factor + S)`

, where `S`

is the value of the rank feature field and `scaling_factor`

is a configurable
scaling factor. Scores are unbounded.

This function only supports rank features that have a positive score impact.

GET /test/_search { "query": { "rank_feature": { "field": "pagerank", "log": { "scaling_factor": 4 } } } }

The `sigmoid`

function is an extension of `saturation`

which adds a configurable
exponent. Scores are computed as `S^exp^ / (S^exp^ + pivot^exp^)`

. Like for the
`saturation`

function, `pivot`

is the value of `S`

that gives a score of `0.5`

and scores are `(0,1)`

.

The `exponent`

must be positive and is typically in `[0.5, 1]`

. A
good value should be computed via training. If you don’t have the opportunity to
do so, we recommend you use the `saturation`

function instead.

GET /test/_search { "query": { "rank_feature": { "field": "pagerank", "sigmoid": { "pivot": 7, "exponent": 0.6 } } } }