304 lines
9.5 KiB
Plaintext
304 lines
9.5 KiB
Plaintext
[[query-dsl-script-score-query]]
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=== Script Score Query
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experimental[]
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The `script_score` allows you to modify the score of documents that are
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retrieved by a query. This can be useful if, for example, a score
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function is computationally expensive and it is sufficient to compute
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the score on a filtered set of documents.
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To use `script_score`, you have to define a query and a script -
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a function to be used to compute a new score for each document returned
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by the query. For more information on scripting see
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<<modules-scripting, scripting documentation>>.
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Here is an example of using `script_score` to assign each matched document
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a score equal to the number of likes divided by 10:
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[source,js]
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--------------------------------------------------
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GET /_search
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{
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"query" : {
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"script_score" : {
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"query" : {
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"match": { "message": "elasticsearch" }
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},
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"script" : {
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"source" : "doc['likes'].value / 10 "
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[setup:twitter]
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==== Accessing the score of a document within a script
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Within a script, you can
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<<modules-scripting-fields#scripting-score, access>>
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the `_score` variable which represents the current relevance score of a
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document.
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==== Predefined functions within a Painless script
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You can use any of the available
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<<painless-api-reference, painless functions>> in the painless script.
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Besides these functions, there are a number of predefined functions
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that can help you with scoring. We suggest you to use them instead of
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rewriting equivalent functions of your own, as these functions try
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to be the most efficient by using the internal mechanisms.
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===== rational
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latexmath:[rational(value,k) = value/(k + value)]
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "rational(doc['likes'].value, 1)"
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}
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--------------------------------------------------
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// NOTCONSOLE
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===== sigmoid
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latexmath:[sigmoid(value, k, a) = value^a/ (k^a + value^a)]
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "sigmoid(doc['likes'].value, 2, 1)"
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}
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--------------------------------------------------
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// NOTCONSOLE
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[[random-functions]]
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===== Random functions
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There are two predefined ways to produce random values:
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1. `randomNotReproducible()` uses `java.util.Random` class
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to generate a random value of the type `long`.
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The generated values are not reproducible between requests' invocations.
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "randomNotReproducible()"
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}
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--------------------------------------------------
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// NOTCONSOLE
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2. `randomReproducible(String seedValue, int seed)` produces
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reproducible random values of type `long`. This function requires
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more computational time and memory than the non-reproducible version.
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A good candidate for the `seedValue` is document field values that
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are unique across documents and already pre-calculated and preloaded
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in the memory. For example, values of the document's `_seq_no` field
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is a good candidate, as documents on the same shard have unique values
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for the `_seq_no` field.
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "randomReproducible(Long.toString(doc['_seq_no'].value), 100)"
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}
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--------------------------------------------------
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// NOTCONSOLE
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A drawback of using `_seq_no` is that generated values change if
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documents are updated. Another drawback is not absolute uniqueness, as
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documents from different shards with the same sequence numbers
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generate the same random values.
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If you need random values to be distinct across different shards,
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you can use a field with unique values across shards,
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such as `_id`, but watch out for the memory usage as all
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these unique values need to be loaded into memory.
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "randomReproducible(doc['_id'].value, 100)"
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}
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--------------------------------------------------
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// NOTCONSOLE
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[[decay-functions]]
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===== Decay functions for numeric fields
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You can read more about decay functions
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<<query-dsl-function-score-query#function-decay, here>>.
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* `double decayNumericLinear(double origin, double scale, double offset, double decay, double docValue)`
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* `double decayNumericExp(double origin, double scale, double offset, double decay, double docValue)`
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* `double decayNumericGauss(double origin, double scale, double offset, double decay, double docValue)`
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "decayNumericLinear(params.origin, params.scale, params.offset, params.decay, doc['dval'].value)",
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"params": { <1>
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"origin": 20,
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"scale": 10,
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"decay" : 0.5,
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"offset" : 0
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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<1> Use `params` to compile a script only once for different values of parameters
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===== Decay functions for geo fields
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* `double decayGeoLinear(String originStr, String scaleStr, String offsetStr, double decay, GeoPoint docValue)`
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* `double decayGeoExp(String originStr, String scaleStr, String offsetStr, double decay, GeoPoint docValue)`
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* `double decayGeoGauss(String originStr, String scaleStr, String offsetStr, double decay, GeoPoint docValue)`
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "decayGeoExp(params.origin, params.scale, params.offset, params.decay, doc['location'].value)",
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"params": {
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"origin": "40, -70.12",
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"scale": "200km",
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"offset": "0km",
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"decay" : 0.2
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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===== Decay functions for date fields
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* `double decayDateLinear(String originStr, String scaleStr, String offsetStr, double decay, JodaCompatibleZonedDateTime docValueDate)`
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* `double decayDateExp(String originStr, String scaleStr, String offsetStr, double decay, JodaCompatibleZonedDateTime docValueDate)`
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* `double decayDateGauss(String originStr, String scaleStr, String offsetStr, double decay, JodaCompatibleZonedDateTime docValueDate)`
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "decayDateGauss(params.origin, params.scale, params.offset, params.decay, doc['date'].value)",
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"params": {
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"origin": "2008-01-01T01:00:00Z",
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"scale": "1h",
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"offset" : "0",
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"decay" : 0.5
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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NOTE: Decay functions on dates are limited to dates in the default format
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and default time zone. Also calculations with `now` are not supported.
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==== Faster alternatives
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Script Score Query calculates the score for every hit (matching document).
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There are faster alternative query types that can efficiently skip
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non-competitive hits:
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* If you want to boost documents on some static fields, use
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<<query-dsl-feature-query, Feature Query>>.
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==== Transition from Function Score Query
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We are deprecating <<query-dsl-function-score-query, Function Score>>, and
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Script Score Query will be a substitute for it.
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Here we describe how Function Score Query's functions can be
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equivalently implemented in Script Score Query:
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===== `script_score`
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What you used in `script_score` of the Function Score query, you
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can copy into the Script Score query. No changes here.
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===== `weight`
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`weight` function can be implemented in the Script Score query through
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the following script:
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "params.weight * _score",
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"params": {
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"weight": 2
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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===== `random_score`
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Use `randomReproducible` and `randomNotReproducible` functions
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as described in <<random-functions, random functions>>.
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===== `field_value_factor`
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`field_value_factor` function can be easily implemented through script:
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "Math.log10(doc['field'].value * params.factor)",
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params" : {
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"factor" : 5
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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For checking if a document has a missing value, you can use
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`doc['field'].size() == 0`. For example, this script will use
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a value `1` if a document doesn't have a field `field`:
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[source,js]
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--------------------------------------------------
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"script" : {
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"source" : "Math.log10((doc['field'].size() == 0 ? 1 : doc['field'].value()) * params.factor)",
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params" : {
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"factor" : 5
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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This table lists how `field_value_factor` modifiers can be implemented
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through a script:
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[cols="<,<",options="header",]
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|=======================================================================
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| Modifier | Implementation in Script Score
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| `none` | -
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| `log` | `Math.log10(doc['f'].value)`
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| `log1p` | `Math.log10(doc['f'].value + 1)`
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| `log2p` | `Math.log10(doc['f'].value + 2)`
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| `ln` | `Math.log(doc['f'].value)`
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| `ln1p` | `Math.log(doc['f'].value + 1)`
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| `ln2p` | `Math.log(doc['f'].value + 2)`
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| `square` | `Math.pow(doc['f'].value, 2)`
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| `sqrt` | `Math.sqrt(doc['f'].value)`
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| `reciprocal` | `1.0 / doc['f'].value`
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|=======================================================================
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===== `decay functions`
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Script Score query has equivalent <<decay-functions, decay functions>>
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that can be used in script.
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