script-score-query.asciidoc

Script score query

Script score

Uses a script to provide a custom score for returned documents.

The script_score query is useful if, for example, a scoring function is expensive and you only need to calculate the score of a filtered set of documents.

Example request

The following script_score query assigns each returned document a score equal to the my-int field value divided by 10.

GET /_search
{
  "query": {
    "script_score": {
      "query": {
        "match": { "message": "elasticsearch" }
      },
      "script": {
        "source": "doc['my-int'].value / 10 "
      }
    }
  }
}

Top-level parameters for script_score

query

(Required, query object) Query used to return documents.

script

(Required, script object) Script used to compute the score of documents returned by the query.

Important

Final relevance scores from the script_score query cannot be negative. To support certain search optimizations, Lucene requires scores be positive or 0.

min_score

(Optional, float) Documents with a score lower than this floating point number are excluded from the search results.

boost

(Optional, float) Documents' scores produced by script are multiplied by boost to produce final documents' scores. Defaults to 1.0.

Notes

Use relevance scores in a script

Within a script, you can {ref}/modules-scripting-fields.html#scripting-score[access] the _score variable which represents the current relevance score of a document.

Predefined functions

You can use any of the available {painless}/painless-contexts.html[painless functions] in your script. You can also use the following predefined functions to customize scoring:

• Saturation

• Sigmoid

• Random score function

• Decay functions for numeric fields

• Decay functions for geo fields

• Decay functions for date fields

• Functions for vector fields

We suggest using these predefined functions instead of writing your own. These functions take advantage of efficiencies from {es}' internal mechanisms.

Saturation

saturation(value,k) = value/(k + value)

"script" : {
    "source" : "saturation(doc['my-int'].value, 1)"
}

Sigmoid

sigmoid(value, k, a) = value^a/ (k^a + value^a)

"script" : {
    "source" : "sigmoid(doc['my-int'].value, 2, 1)"
}

Random score function

random_score function generates scores that are uniformly distributed from 0 up to but not including 1.

randomScore function has the following syntax: randomScore(<seed>, <fieldName>). It has a required parameter - seed as an integer value, and an optional parameter - fieldName as a string value.

"script" : {
    "source" : "randomScore(100, '_seq_no')"
}

If the fieldName parameter is omitted, the internal Lucene document ids will be used as a source of randomness. This is very efficient, but unfortunately not reproducible since documents might be renumbered by merges.

"script" : {
    "source" : "randomScore(100)"
}

Note that documents that are within the same shard and have the same value for field will get the same score, so it is usually desirable to use a field that has unique values for all documents across a shard. A good default choice might be to use the _seq_no field, whose only drawback is that scores will change if the document is updated since update operations also update the value of the _seq_no field.

Decay functions for numeric fields

You can read more about decay functions {ref}/query-dsl-function-score-query.html#function-decay[here].

• double decayNumericLinear(double origin, double scale, double offset, double decay, double docValue)

• double decayNumericExp(double origin, double scale, double offset, double decay, double docValue)

• double decayNumericGauss(double origin, double scale, double offset, double decay, double docValue)

"script" : {
    "source" : "decayNumericLinear(params.origin, params.scale, params.offset, params.decay, doc['dval'].value)",
    "params": { (1)
        "origin": 20,
        "scale": 10,
        "decay" : 0.5,
        "offset" : 0
    }
}

1. Using params allows to compile the script only once, even if params change.

Decay functions for geo fields

• double decayGeoLinear(String originStr, String scaleStr, String offsetStr, double decay, GeoPoint docValue)

• double decayGeoExp(String originStr, String scaleStr, String offsetStr, double decay, GeoPoint docValue)

• double decayGeoGauss(String originStr, String scaleStr, String offsetStr, double decay, GeoPoint docValue)

"script" : {
    "source" : "decayGeoExp(params.origin, params.scale, params.offset, params.decay, doc['location'].value)",
    "params": {
        "origin": "40, -70.12",
        "scale": "200km",
        "offset": "0km",
        "decay" : 0.2
    }
}

Decay functions for date fields

• double decayDateLinear(String originStr, String scaleStr, String offsetStr, double decay, JodaCompatibleZonedDateTime docValueDate)

• double decayDateExp(String originStr, String scaleStr, String offsetStr, double decay, JodaCompatibleZonedDateTime docValueDate)

• double decayDateGauss(String originStr, String scaleStr, String offsetStr, double decay, JodaCompatibleZonedDateTime docValueDate)

"script" : {
    "source" : "decayDateGauss(params.origin, params.scale, params.offset, params.decay, doc['date'].value)",
    "params": {
        "origin": "2008-01-01T01:00:00Z",
        "scale": "1h",
        "offset" : "0",
        "decay" : 0.5
    }
}

Note	Decay functions on dates are limited to dates in the default format and default time zone. Also calculations with now are not supported.

Functions for vector fields

Functions for vector fields are accessible through script_score query.

Allow expensive queries

Script score queries will not be executed if search.allow_expensive_queries is set to false.

Faster alternatives

The script_score query calculates the score for every matching document, or hit. There are faster alternative query types that can efficiently skip non-competitive hits:

• If you want to boost documents on some static fields, use the rank_feature query.

• If you want to boost documents closer to a date or geographic point, use the distance_feature query.

Transition from the function score query

We recommend using the script_score query instead of function_score query for the simplicity of the script_score query.

You can implement the following functions of the function_score query using the script_score query:

• script_score

• weight

• random_score

• field_value_factor

• decay functions

script_score

What you used in script_score of the Function Score query, you can copy into the Script Score query. No changes here.

weight

weight function can be implemented in the Script Score query through the following script:

"script" : {
    "source" : "params.weight * _score",
    "params": {
        "weight": 2
    }
}

random_score

Use randomScore function as described in random score function.

field_value_factor

field_value_factor function can be easily implemented through script:

"script" : {
    "source" : "Math.log10(doc['field'].value * params.factor)",
    "params" : {
        "factor" : 5
    }
}

For checking if a document has a missing value, you can use doc['field'].size() == 0. For example, this script will use a value 1 if a document doesn’t have a field field:

"script" : {
    "source" : "Math.log10((doc['field'].size() == 0 ? 1 : doc['field'].value()) * params.factor)",
    "params" : {
        "factor" : 5
    }
}

This table lists how field_value_factor modifiers can be implemented through a script:

Modifier	Implementation in Script Score
none	-
log	Math.log10(doc['f'].value)
log1p	Math.log10(doc['f'].value + 1)
log2p	Math.log10(doc['f'].value + 2)
ln	Math.log(doc['f'].value)
ln1p	Math.log(doc['f'].value + 1)
ln2p	Math.log(doc['f'].value + 2)
square	Math.pow(doc['f'].value, 2)
sqrt	Math.sqrt(doc['f'].value)
reciprocal	1.0 / doc['f'].value

decay functions

The script_score query has equivalent decay functions that can be used in scripts.

{es-repo-dir}/vectors/vector-functions.asciidoc

Explain request

Using an explain request provides an explanation of how the parts of a score were computed. The script_score query can add its own explanation by setting the explanation parameter:

GET /my-index-000001/_explain/0
{
  "query": {
    "script_score": {
      "query": {
        "match": { "message": "elasticsearch" }
      },
      "script": {
        "source": """
          long count = doc['count'].value;
          double normalizedCount = count / 10;
          if (explanation != null) {
            explanation.set('normalized count = count / 10 = ' + count + ' / 10 = ' + normalizedCount);
          }
          return normalizedCount;
        """
      }
    }
  }
}

Note that the explanation will be null when using in a normal _search request, so having a conditional guard is best practice.