80 lines
2.2 KiB
Plaintext
80 lines
2.2 KiB
Plaintext
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[[query-dsl-fuzzy-query]]
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=== Fuzzy Query
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A fuzzy based query that uses similarity based on Levenshtein (edit
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distance) algorithm.
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Warning: this query is not very scalable with its default prefix length
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of 0 - in this case, *every* term will be enumerated and cause an edit
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score calculation or `max_expansions` is not set.
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Here is a simple example:
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[source,js]
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--------------------------------------------------
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{
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"fuzzy" : { "user" : "ki" }
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}
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--------------------------------------------------
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More complex settings can be set (the values here are the default
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values):
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[source,js]
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--------------------------------------------------
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{
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"fuzzy" : {
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"user" : {
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"value" : "ki",
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"boost" : 1.0,
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"min_similarity" : 0.5,
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"prefix_length" : 0
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}
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}
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}
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--------------------------------------------------
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The `max_expansions` parameter (unbounded by default) controls the
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number of terms the fuzzy query will expand to.
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[float]
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==== Numeric / Date Fuzzy
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`fuzzy` query on a numeric field will result in a range query "around"
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the value using the `min_similarity` value. For example:
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[source,js]
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--------------------------------------------------
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{
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"fuzzy" : {
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"price" : {
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"value" : 12,
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"min_similarity" : 2
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}
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}
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}
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--------------------------------------------------
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Will result in a range query between 10 and 14. Same applies to dates,
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with support for time format for the `min_similarity` field:
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[source,js]
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--------------------------------------------------
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{
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"fuzzy" : {
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"created" : {
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"value" : "2010-02-05T12:05:07",
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"min_similarity" : "1d"
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}
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}
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}
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--------------------------------------------------
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In the mapping, numeric and date types now allow to configure a
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`fuzzy_factor` mapping value (defaults to 1), which will be used to
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multiply the fuzzy value by it when used in a `query_string` type query.
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For example, for dates, a fuzzy factor of "1d" will result in
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multiplying whatever fuzzy value provided in the min_similarity by it.
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Note, this is explicitly supported since query_string query only allowed
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for similarity valued between 0.0 and 1.0.
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