org.elasticsearch.search.suggest.term

Class TermSuggestionBuilder

java.lang.Object

org.elasticsearch.action.support.ToXContentToBytes

org.elasticsearch.search.suggest.SuggestBuilder.SuggestionBuilder<TermSuggestionBuilder>

org.elasticsearch.search.suggest.term.TermSuggestionBuilder

All Implemented Interfaces:

ToXContent

public class TermSuggestionBuilder
extends SuggestBuilder.SuggestionBuilder<TermSuggestionBuilder>

Defines the actual suggest command. Each command uses the global options unless defined in the suggestion itself. All options are the same as the global options, but are only applicable for this suggestion.

Nested Class Summary

Nested classes/interfaces inherited from interface org.elasticsearch.common.xcontent.ToXContent

ToXContent.DelegatingMapParams, ToXContent.MapParams, ToXContent.Params

Field Summary

Fields inherited from interface org.elasticsearch.common.xcontent.ToXContent

EMPTY_PARAMS

Constructor Summary

Constructors

Constructor and Description
TermSuggestionBuilder(String name)

Method Summary

Methods

Modifier and Type	Method and Description
XContentBuilder	innerToXContent(XContentBuilder builder, ToXContent.Params params)
TermSuggestionBuilder	maxEdits(Integer maxEdits) Sets the maximum edit distance candidate suggestions can have in order to be considered as a suggestion.
TermSuggestionBuilder	maxInspections(Integer maxInspections) A factor that is used to multiply with the size in order to inspect more candidate suggestions.
TermSuggestionBuilder	maxTermFreq(float maxTermFreq) Sets a maximum threshold in number of documents a suggest text token can exist in order to be corrected.
TermSuggestionBuilder	minDocFreq(float minDocFreq) Sets a minimal threshold in number of documents a suggested term should appear in.
TermSuggestionBuilder	minWordLength(int minWordLength) The minimum length a suggest text term must have in order to be corrected.
TermSuggestionBuilder	prefixLength(int prefixLength) Sets the number of minimal prefix characters that must match in order be a candidate suggestion.
TermSuggestionBuilder	setAccuracy(float accuracy) s how similar the suggested terms at least need to be compared to the original suggest text tokens.
TermSuggestionBuilder	sort(String sort) Sets how to sort the suggest terms per suggest text token.
TermSuggestionBuilder	stringDistance(String stringDistance) Sets what string distance implementation to use for comparing how similar suggested terms are.
TermSuggestionBuilder	suggestMode(String suggestMode) The global suggest mode controls what suggested terms are included or controls for what suggest text tokens, terms should be suggested for.

Methods inherited from class org.elasticsearch.search.suggest.SuggestBuilder.SuggestionBuilder

addCategory, addCategory, addContextField, addContextField, addGeoLocation, addGeoLocation, addGeoLocationWithPrecision, analyzer, field, shardSize, size, text, toXContent

Methods inherited from class org.elasticsearch.action.support.ToXContentToBytes

buildAsBytes, buildAsBytes, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

TermSuggestionBuilder

public TermSuggestionBuilder(String name)

Parameters:

name - The name of this suggestion. This is a required parameter.

Method Detail

suggestMode

public TermSuggestionBuilder suggestMode(String suggestMode)

The global suggest mode controls what suggested terms are included or controls for what suggest text tokens, terms should be suggested for. Three possible values can be specified:

1. missing - Only suggest terms in the suggest text that aren't in the index. This is the default.
2. popular - Only suggest terms that occur in more docs then the original suggest text term.
3. always - Suggest any matching suggest terms based on tokens in the suggest text.

setAccuracy

public TermSuggestionBuilder setAccuracy(float accuracy)

s how similar the suggested terms at least need to be compared to the original suggest text tokens. A value between 0 and 1 can be specified. This value will be compared to the string distance result of each candidate spelling correction.

Default is 0.5

sort

public TermSuggestionBuilder sort(String sort)

Sets how to sort the suggest terms per suggest text token. Two possible values:

1. score - Sort should first be based on score, then document frequency and then the term itself.
2. frequency - Sort should first be based on document frequency, then scotr and then the term itself.

What the score is depends on the suggester being used.

stringDistance

public TermSuggestionBuilder stringDistance(String stringDistance)

Sets what string distance implementation to use for comparing how similar suggested terms are. Four possible values can be specified:

1. internal - This is the default and is based on damerau_levenshtein, but highly optimized for comparing string distance for terms inside the index.
2. damerau_levenshtein - String distance algorithm based on Damerau-Levenshtein algorithm.
3. levenstein - String distance algorithm based on Levenstein edit distance algorithm.
4. jarowinkler - String distance algorithm based on Jaro-Winkler algorithm.
5. ngram - String distance algorithm based on character n-grams.

maxEdits

public TermSuggestionBuilder maxEdits(Integer maxEdits)

Sets the maximum edit distance candidate suggestions can have in order to be considered as a suggestion. Can only be a value between 1 and 2. Any other value result in an bad request error being thrown. Defaults to 2.

maxInspections

public TermSuggestionBuilder maxInspections(Integer maxInspections)

A factor that is used to multiply with the size in order to inspect more candidate suggestions. Can improve accuracy at the cost of performance. Defaults to 5.

maxTermFreq

public TermSuggestionBuilder maxTermFreq(float maxTermFreq)

Sets a maximum threshold in number of documents a suggest text token can exist in order to be corrected. Can be a relative percentage number (e.g 0.4) or an absolute number to represent document frequencies. If an value higher than 1 is specified then fractional can not be specified. Defaults to 0.01.

This can be used to exclude high frequency terms from being suggested. High frequency terms are usually spelled correctly on top of this this also improves the suggest performance.

prefixLength

public TermSuggestionBuilder prefixLength(int prefixLength)

Sets the number of minimal prefix characters that must match in order be a candidate suggestion. Defaults to 1. Increasing this number improves suggest performance. Usually misspellings don't occur in the beginning of terms.

minWordLength

public TermSuggestionBuilder minWordLength(int minWordLength)

The minimum length a suggest text term must have in order to be corrected. Defaults to 4.

minDocFreq

public TermSuggestionBuilder minDocFreq(float minDocFreq)

Sets a minimal threshold in number of documents a suggested term should appear in. This can be specified as an absolute number or as a relative percentage of number of documents. This can improve quality by only suggesting high frequency terms. Defaults to 0f and is not enabled. If a value higher than 1 is specified then the number cannot be fractional.

innerToXContent

public XContentBuilder innerToXContent(XContentBuilder builder,
                              ToXContent.Params params)
                                throws IOException

Specified by:

innerToXContent in class SuggestBuilder.SuggestionBuilder<TermSuggestionBuilder>

Throws:

IOException