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Expose Lucene's FeatureField. (#30618)
Lucene has a new `FeatureField` which gives the ability to record numeric features as term frequencies. Its main benefit is that it allows to boost queries with the values of these features and efficiently skip non-competitive documents at the same time using block-max WAND and indexed impacts.
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[[feature]] | ||
=== Feature datatype | ||
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A `feature` field can index numbers so that they can later be used to boost | ||
documents in queries with a <<query-dsl-feature-query,`feature`>> query. | ||
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[source,js] | ||
-------------------------------------------------- | ||
PUT my_index | ||
{ | ||
"mappings": { | ||
"_doc": { | ||
"properties": { | ||
"pagerank": { | ||
"type": "feature" <1> | ||
}, | ||
"url_length": { | ||
"type": "feature", | ||
"positive_score_impact": false <2> | ||
} | ||
} | ||
} | ||
} | ||
} | ||
PUT my_index/_doc/1 | ||
{ | ||
"pagerank": 8, | ||
"url_length": 22 | ||
} | ||
GET my_index/_search | ||
{ | ||
"query": { | ||
"feature": { | ||
"field": "pagerank" | ||
} | ||
} | ||
} | ||
-------------------------------------------------- | ||
// CONSOLE | ||
<1> Feature fields must use the `feature` field type | ||
<2> Features that correlate negatively with the score need to declare it | ||
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NOTE: `feature` fields only support single-valued fields and strictly positive | ||
values. Multi-valued fields and negative values will be rejected. | ||
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NOTE: `feature` fields do not support querying, sorting or aggregating. They may | ||
only be used within <<query-dsl-feature-query,`feature`>> queries. | ||
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NOTE: `feature` fields only preserve 9 significant bits for the precision, which | ||
translates to a relative error of about 0.4%. | ||
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Features that correlate negatively with the score should set | ||
`positive_score_impact` to `false` (defaults to `true`). This will be used by | ||
the <<query-dsl-feature-query,`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. |
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[[query-dsl-feature-query]] | ||
=== Feature Query | ||
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The `feature` query is a specialized query that only works on | ||
<<feature,`feature`>> fields. Its goal is to boost the score of documents based | ||
on the values of numeric features. It is typically put in a `should` clause of | ||
a <<query-dsl-bool-query,`bool`>> query so that its score is added to the score | ||
of the query. | ||
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Compared to using <<query-dsl-function-score-query,`function_score`>> or other | ||
ways to modify the score, this query has the benefit of being able to | ||
efficiently skip non-competitive hits when | ||
<<search-uri-request,`track_total_hits`>> is set to `false`. Speedups may be | ||
spectacular. | ||
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Here is an example: | ||
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[source,js] | ||
-------------------------------------------------- | ||
PUT test | ||
{ | ||
"mappings": { | ||
"_doc": { | ||
"properties": { | ||
"pagerank": { | ||
"type": "feature" | ||
}, | ||
"url_length": { | ||
"type": "feature", | ||
"positive_score_impact": false | ||
} | ||
} | ||
} | ||
} | ||
} | ||
PUT test/_doc/1 | ||
{ | ||
"pagerank": 10, | ||
"url_length": 50 | ||
} | ||
PUT test/_doc/2 | ||
{ | ||
"pagerank": 100, | ||
"url_length": 20 | ||
} | ||
POST test/_refresh | ||
GET test/_search | ||
{ | ||
"query": { | ||
"feature": { | ||
"field": "pagerank" | ||
} | ||
} | ||
} | ||
GET test/_search | ||
{ | ||
"query": { | ||
"feature": { | ||
"field": "url_length" | ||
} | ||
} | ||
} | ||
-------------------------------------------------- | ||
// CONSOLE | ||
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[float] | ||
=== Supported functions | ||
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The `feature` query supports 3 functions in order to boost scores using the | ||
values of features. If you do not know where to start, we recommend that you | ||
start with the `saturation` function, which is the default when no function is | ||
provided. | ||
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[float] | ||
==== Saturation | ||
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This function gives a score that is equal to `S / (S + pivot)` where `S` is the | ||
value of the feature 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 is +(0, 1)+. | ||
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If the feature has a negative score impact then the function will be computed as | ||
`pivot / (S + pivot)`, which decreases when `S` increases. | ||
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[source,js] | ||
-------------------------------------------------- | ||
GET test/_search | ||
{ | ||
"query": { | ||
"feature": { | ||
"field": "pagerank", | ||
"saturation": { | ||
"pivot": 8 | ||
} | ||
} | ||
} | ||
} | ||
-------------------------------------------------- | ||
// CONSOLE | ||
// TEST[continued] | ||
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If +pivot+ is not supplied then Elasticsearch will compute a default value that | ||
will be approximately equal to the geometric mean of all feature values that | ||
exist in the index. We recommend this if you haven't had the opportunity to | ||
train a good pivot value. | ||
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[source,js] | ||
-------------------------------------------------- | ||
GET test/_search | ||
{ | ||
"query": { | ||
"feature": { | ||
"field": "pagerank", | ||
"saturation": {} | ||
} | ||
} | ||
} | ||
-------------------------------------------------- | ||
// CONSOLE | ||
// TEST[continued] | ||
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[float] | ||
==== Logarithm | ||
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This function gives a score that is equal to `log(scaling_factor + S)` where | ||
`S` is the value of the feature and `scaling_factor` is a configurable scaling | ||
factor. Scores are unbounded. | ||
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This function only supports features that have a positive score impact. | ||
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[source,js] | ||
-------------------------------------------------- | ||
GET test/_search | ||
{ | ||
"query": { | ||
"feature": { | ||
"field": "pagerank", | ||
"log": { | ||
"scaling_factor": 4 | ||
} | ||
} | ||
} | ||
} | ||
-------------------------------------------------- | ||
// CONSOLE | ||
// TEST[continued] | ||
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[float] | ||
==== Sigmoid | ||
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This 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 in +(0, 1)+. | ||
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`exponent` must be positive, but is typically in +[0.5, 1]+. A good value should | ||
be computed via traning. If you don't have the opportunity to do so, we recommend | ||
that you stick to the `saturation` function instead. | ||
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[source,js] | ||
-------------------------------------------------- | ||
GET test/_search | ||
{ | ||
"query": { | ||
"feature": { | ||
"field": "pagerank", | ||
"sigmoid": { | ||
"pivot": 7, | ||
"exponent": 0.6 | ||
} | ||
} | ||
} | ||
} | ||
-------------------------------------------------- | ||
// CONSOLE | ||
// TEST[continued] |
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