elastic.js: Module: MatchQuery

Module

MatchQuery


        MatchQuery ( field, qstr )

A Query that appects text, analyzes it, generates internal query based on the MatchQuery type.

Parameters: field <String> the document field/field to query against
qstr <String> the query string

Method Summary

Returns	Name	Description
`String`	`_type()`	The type of ejs object. For internal use only.
`Object`	`analyzer(analyzer)`	Sets the analyzer name used to analyze the `Query` object.
`Object`	`boost(boost)`	Sets the boost value for documents matching the `Query`.
`Object`	`cutoffFrequency(freq)`	Sets the maximum threshold/frequency to be considered a low frequency term in a `CommonTermsQuery`. Set to a value between 0 and 1.
`Object`	`fuzziness(fuzz)`	Sets the fuzziness value for the `Query`.
`Object`	`fuzzyRewrite(m)`	Sets fuzzy rewrite method. Valid values are: constant_score_auto - tries to pick the best constant-score rewrite method based on term and document counts from the query scoring_boolean - translates each term into boolean should and keeps the scores as computed by the query constant_score_boolean - same as scoring_boolean, expect no scores are computed. constant_score_filter - first creates a private Filter, by visiting each term in sequence and marking all docs for that term top_terms_boost_N - first translates each term into boolean should and scores are only computed as the boost using the top N scoring terms. Replace N with an integer value. top_terms_N - first translates each term into boolean should and keeps the scores as computed by the query. Only the top N scoring terms are used. Replace N with an integer value. Default is constant_score_auto. This is an advanced option, use with care.
`Object`	`fuzzyTranspositions(trueFalse)`	Set to false to use classic Levenshtein edit distance in the fuzzy query.
`Object`	`lenient(trueFalse)`	Enables lenient parsing of the query string.
`Object`	`maxExpansions(e)`	Sets the max expansions of a fuzzy `MatchQuery`.
`Object`	`minimumShouldMatch(minMatch)`	Sets a string value controlling how many "should" clauses in the resulting `Query` should match.
`Object`	`minimumShouldMatch(minMatch)`	Sets a percent value controlling how many "should" clauses in the resulting `Query` should match.
`Object`	`operator(op)`	Sets default operator of the `Query`. Default: or.
`Object`	`prefixLength(l)`	Sets the prefix length for a fuzzy prefix `MatchQuery`.
`Object`	`query(qstr)`	Sets the query string for the `Query`.
`Object`	`rewrite(m)`	Sets rewrite method. Valid values are: constant_score_auto - tries to pick the best constant-score rewrite method based on term and document counts from the query scoring_boolean - translates each term into boolean should and keeps the scores as computed by the query constant_score_boolean - same as scoring_boolean, expect no scores are computed. constant_score_filter - first creates a private Filter, by visiting each term in sequence and marking all docs for that term top_terms_boost_N - first translates each term into boolean should and scores are only computed as the boost using the top N scoring terms. Replace N with an integer value. top_terms_N - first translates each term into boolean should and keeps the scores as computed by the query. Only the top N scoring terms are used. Replace N with an integer value. Default is constant_score_auto. This is an advanced option, use with care.
`Object`	`slop(slop)`	Sets the default slop for phrases. If zero, then exact phrase matches are required. Default: 0.
`String`	`toJSON()`	Retrieves the internal `query` object. This is typically used by internal API functions so use with caution.
`Object`	`type(type)`	Sets the type of the `MatchQuery`. Valid values are boolean, phrase, and phrase_prefix.
`Object`	`zeroTermsQuery(q)`	Sets what happens when no terms match. Valid values are "all" or "none".

Method Detail

_type


        String _type ( )

The type of ejs object. For internal use only.

Returns: the type of object

analyzer


        Object analyzer ( analyzer )

Sets the analyzer name used to analyze the Query object.

Parameters: analyzer <String> A valid analyzer name.
Returns: returns this so that calls can be chained.

boost


        Object boost ( boost )

Sets the boost value for documents matching the Query.

Parameters: boost <Number> A positive double value.
Returns: returns this so that calls can be chained.

cutoffFrequency


        Object cutoffFrequency ( freq )

Sets the maximum threshold/frequency to be considered a low frequency term in a CommonTermsQuery. Set to a value between 0 and 1.

Parameters: freq <Number> A positive double value.
Returns: returns this so that calls can be chained.

fuzziness


        Object fuzziness ( fuzz )

Sets the fuzziness value for the Query.

Parameters: fuzz <Double> A double value between 0.0 and 1.0.
Returns: returns this so that calls can be chained.

fuzzyRewrite


        Object fuzzyRewrite ( m )

Sets fuzzy rewrite method. Valid values are: constant_score_auto - tries to pick the best constant-score rewrite method based on term and document counts from the query scoring_boolean - translates each term into boolean should and keeps the scores as computed by the query constant_score_boolean - same as scoring_boolean, expect no scores are computed. constant_score_filter - first creates a private Filter, by visiting each term in sequence and marking all docs for that term top_terms_boost_N - first translates each term into boolean should and scores are only computed as the boost using the top N scoring terms. Replace N with an integer value. top_terms_N - first translates each term into boolean should and keeps the scores as computed by the query. Only the top N scoring terms are used. Replace N with an integer value. Default is constant_score_auto. This is an advanced option, use with care.

Parameters: m <String> The rewrite method as a string.
Returns: returns this so that calls can be chained.

fuzzyTranspositions


        Object fuzzyTranspositions ( trueFalse )

Set to false to use classic Levenshtein edit distance in the fuzzy query.

Parameters: trueFalse <Boolean> A boolean value
Returns: returns this so that calls can be chained.

lenient


        Object lenient ( trueFalse )

Enables lenient parsing of the query string.

Parameters: trueFalse <Boolean> A boolean value
Returns: returns this so that calls can be chained.

maxExpansions


        Object maxExpansions ( e )

Sets the max expansions of a fuzzy MatchQuery.

Parameters: e <Integer> A positive integer value.
Returns: returns this so that calls can be chained.

minimumShouldMatch


        Object minimumShouldMatch ( minMatch )

Sets a string value controlling how many "should" clauses in the resulting Query should match.

Parameters: minMatch <String> A min should match parameter.
Returns: returns this so that calls can be chained.

minimumShouldMatch


        Object minimumShouldMatch ( minMatch )

Sets a percent value controlling how many "should" clauses in the resulting Query should match.

Parameters: minMatch <String> A min should match parameter.
Returns: returns this so that calls can be chained.

operator


        Object operator ( op )

Sets default operator of the Query. Default: or.

Parameters: op <String> Any of "and" or "or", no quote characters.
Returns: returns this so that calls can be chained.

prefixLength


        Object prefixLength ( l )

Sets the prefix length for a fuzzy prefix MatchQuery.

Parameters: l <Integer> A positive integer length value.
Returns: returns this so that calls can be chained.

query


        Object query ( qstr )

Sets the query string for the Query.

Parameters: qstr <String> The query string to search for.
Returns: returns this so that calls can be chained.

rewrite


        Object rewrite ( m )

Sets rewrite method. Valid values are: constant_score_auto - tries to pick the best constant-score rewrite method based on term and document counts from the query scoring_boolean - translates each term into boolean should and keeps the scores as computed by the query constant_score_boolean - same as scoring_boolean, expect no scores are computed. constant_score_filter - first creates a private Filter, by visiting each term in sequence and marking all docs for that term top_terms_boost_N - first translates each term into boolean should and scores are only computed as the boost using the top N scoring terms. Replace N with an integer value. top_terms_N - first translates each term into boolean should and keeps the scores as computed by the query. Only the top N scoring terms are used. Replace N with an integer value. Default is constant_score_auto. This is an advanced option, use with care.

Parameters: m <String> The rewrite method as a string.
Returns: returns this so that calls can be chained.

slop


        Object slop ( slop )

Sets the default slop for phrases. If zero, then exact phrase matches are required. Default: 0.

Parameters: slop <Integer> A positive integer value.
Returns: returns this so that calls can be chained.

toJSON


        String toJSON ( )

Retrieves the internal query object. This is typically used by internal API functions so use with caution.

Returns: returns this object's internal query property.

type


        Object type ( type )

Sets the type of the MatchQuery. Valid values are boolean, phrase, and phrase_prefix.

Parameters: type <String> Any of boolean, phrase, phrase_prefix.
Returns: returns this so that calls can be chained.

zeroTermsQuery


        Object zeroTermsQuery ( q )

Sets what happens when no terms match. Valid values are "all" or "none".

Parameters: q <String> A no match action, "all" or "none".
Returns: returns this so that calls can be chained.

ejs ⟩ MatchQuery

Module

MatchQuery

Method Summary

Method Detail

_type

analyzer

boost

cutoffFrequency

fuzziness

fuzzyRewrite

fuzzyTranspositions

lenient

maxExpansions

minimumShouldMatch

minimumShouldMatch

operator

prefixLength

query

rewrite

slop

toJSON

type

zeroTermsQuery

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