Struct elasticsearch_dsl::search::queries::term_level::FuzzyQuery[−][src]

pub struct FuzzyQuery { /* fields omitted */ }

Expand description

Returns documents that contain terms similar to the search term, as measured by a Levenshtein edit distance.

An edit distance is the number of one-character changes needed to turn one term into another. These changes can include:

Changing a character (box → fox)
Removing a character (black → lack)
Inserting a character (sic → sick)
Transposing two adjacent characters (act → cat) To find similar terms, the fuzzy query creates a set of all possible variations, or expansions, of the search term within a specified edit distance. The query then returns exact matches for each expansion.

To create a fuzzy query with numeric values:

Query::fuzzy("test", 123);

To create a fuzzy query with string values and optional fields:

Query::fuzzy("test", "username")
    .boost(2)
    .name("test");

https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-fuzzy-query.html

Implementations

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impl FuzzyQuery

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pub fn fuzziness(self, fuzziness: impl Into<Fuzziness>) -> Self

Maximum edit distance allowed for matching. See Fuzziness for valid values and more information. See Fuzziness in the match query for an example.

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pub fn max_expansions(self, max_expansions: u8) -> Self

Maximum number of terms to which the query will expand. Defaults to 50.

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pub fn prefix_length(self, prefix_length: u8) -> Self

Number of beginning characters left unchanged for fuzzy matching. Defaults to 0.

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pub fn transpositions(self, transpositions: bool) -> Self

Indicates whether edits include transpositions of two adjacent characters (ab → ba). Defaults to true

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pub fn rewrite(self, rewrite: Rewrite) -> Self

Method used to rewrite the query. For valid values and more information, see the rewrite parameter.

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pub fn boost(self, boost: impl TryInto<Boost>) -> Self

Floating point number used to decrease or increase the relevance scores of a query. Defaults to 1.0.

You can use the boost parameter to adjust relevance scores for searches containing two or more queries.

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.

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pub fn name(self, name: impl Into<String>) -> Self

You can use named queries to track which queries matched returned documents. If named queries are used, the response includes a matched_queries property for each hit.

https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html#named-queries