@jmaitrehenry/elastic-builder
Version:
A JavaScript implementation of the elasticsearch Query DSL
241 lines (218 loc) • 9.08 kB
JavaScript
'use strict';
const isNil = require('lodash.isnil');
const {
consts: { SUGGEST_MODE_SET, STRING_DISTANCE_SET },
util: { invalidParam }
} = require('../core');
const AnalyzedSuggesterBase = require('./analyzed-suggester-base');
const ES_REF_URL =
'https://www.elastic.co/guide/en/elasticsearch/reference/current/search-suggesters-term.html';
const invalidSortParam = invalidParam(
ES_REF_URL,
'sort',
"'score' or 'frequency'"
);
const invalidSuggestModeParam = invalidParam(
ES_REF_URL,
'suggest_mode',
SUGGEST_MODE_SET
);
const invalidStringDistanceParam = invalidParam(
ES_REF_URL,
'string_distance',
STRING_DISTANCE_SET
);
/**
* The term suggester suggests terms based on edit distance.
* The provided suggest text is analyzed before terms are suggested.
* The suggested terms are provided per analyzed suggest text token.
* The term suggester doesn’t take the query into account that is part of request.
*
* [Elasticsearch reference](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-suggesters-term.html)
*
* @example
* const suggest = esb.termSuggester(
* 'my-suggestion',
* 'message',
* 'tring out Elasticsearch'
* );
*
* @param {string} name The name of the Suggester, an arbitrary identifier
* @param {string=} field The field to fetch the candidate suggestions from.
* @param {string=} txt A string to get suggestions for.
*
* @throws {Error} if `name` is empty
*
* @extends AnalyzedSuggesterBase
*/
class TermSuggester extends AnalyzedSuggesterBase {
// eslint-disable-next-line require-jsdoc
constructor(name, field, txt) {
super('term', name, field, txt);
}
/**
* Sets the sort to control how suggestions should be sorted per
* suggest text term.
*
* Two possible values:
* - `score`: Sort by score first, then document frequency and
* then the term itself.
* - `frequency`: Sort by document frequency first, then similarity
* score and then the term itself.
*
* @param {string} sort Can be `score` or `frequency`
* @returns {TermSuggester} returns `this` so that calls can be chained.
* @throws {Error} If `sort` is neither `score` nor `frequency`.
*/
sort(sort) {
if (isNil(sort)) invalidSortParam(sort);
const sortLower = sort.toLowerCase();
if (sortLower !== 'score' && sortLower !== 'frequency') {
invalidSortParam(sort);
}
this._suggestOpts.sort = sortLower;
return this;
}
/**
* Sets the suggest mode which controls what suggestions are included
* or controls for what suggest text terms, suggestions should be suggested.
*
* Three possible values can be specified:
* - `missing`: Only provide suggestions for suggest text terms that
* are not in the index. This is the default.
* - `popular`: Only suggest suggestions that occur in more docs
* than the original suggest text term.
* - `always`: Suggest any matching suggestions based on terms in the suggest text.
*
* @param {string} mode Can be `missing`, `popular` or `always`
* @returns {TermSuggester} returns `this` so that calls can be chained.
* @throws {Error} If `mode` is not one of `missing`, `popular` or `always`.
*/
suggestMode(mode) {
if (isNil(mode)) invalidSuggestModeParam(mode);
const modeLower = mode.toLowerCase();
if (!SUGGEST_MODE_SET.has(modeLower)) {
invalidSuggestModeParam(mode);
}
this._suggestOpts.suggest_mode = modeLower;
return this;
}
/**
* 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.
*
* @param {number} maxEdits Value between 1 and 2. Defaults to 2.
* @returns {TermSuggester} returns `this` so that calls can be chained.
*/
maxEdits(maxEdits) {
this._suggestOpts.max_edits = maxEdits;
return this;
}
/**
* Sets the number of minimal prefix characters that must match in order
* to be a candidate suggestions. Defaults to 1.
*
* Increasing this number improves spellcheck performance.
* Usually misspellings don't occur in the beginning of terms.
*
* @param {number} len The number of minimal prefix characters that must match in order
* to be a candidate suggestions. Defaults to 1.
* @returns {TermSuggester} returns `this` so that calls can be chained.
*/
prefixLength(len) {
this._suggestOpts.prefix_length = len;
return this;
}
/**
* Sets the minimum length a suggest text term must have in order to be included.
* Defaults to 4.
*
* @param {number} len The minimum length a suggest text term must have in order
* to be included. Defaults to 4.
* @returns {TermSuggester} returns `this` so that calls can be chained.
*/
minWordLength(len) {
this._suggestOpts.min_word_length = len;
return this;
}
/**
* Sets factor that is used to multiply with the `shards_size` in order to inspect
* more candidate spell corrections on the shard level.
* Can improve accuracy at the cost of performance. Defaults to 5.
*
* @param {number} maxInspections Factor used to multiple with `shards_size` in
* order to inspect more candidate spell corrections on the shard level.
* Defaults to 5
* @returns {TermSuggester} returns `this` so that calls can be chained.
*/
maxInspections(maxInspections) {
this._suggestOpts.max_inspections = maxInspections;
return this;
}
/**
* Sets the minimal threshold in number of documents a suggestion 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. The shard level document
* frequencies are used for this option.
*
* @param {number} limit Threshold in number of documents a suggestion
* should appear in. Defaults to 0f and is not enabled.
* @returns {TermSuggester} returns `this` so that calls can be chained.
*/
minDocFreq(limit) {
this._suggestOpts.min_doc_freq = limit;
return this;
}
/**
* Sets the maximum threshold in number of documents a suggest text token can
* exist in order to be included. 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 0.01f.
* This can be used to exclude high frequency terms from being spellchecked.
* High frequency terms are usually spelled correctly on top of this also
* improves the spellcheck performance. The shard level document frequencies are
* used for this option.
*
* @param {number} limit Maximum threshold in number of documents a suggest text
* token can exist in order to be included. Defaults to 0.01f.
* @returns {TermSuggester} returns `this` so that calls can be chained.
*/
maxTermFreq(limit) {
this._suggestOpts.max_term_freq = limit;
return this;
}
/**
* Sets the string distance implementation to use for comparing how similar
* suggested terms are.
*
* Five possible values can be specified:
* - `internal`: The default based on `damerau_levenshtein` but highly optimized for
* comparing string distance for terms inside the index.
* - `damerau_levenshtein`: String distance algorithm based on Damerau-Levenshtein
* algorithm.
* - `levenstein`: String distance algorithm based on Levenstein edit distance
* algorithm.
* - `jarowinkler`: String distance algorithm based on Jaro-Winkler algorithm.
* - `ngram`: String distance algorithm based on character n-grams.
*
* @param {string} implMethod One of `internal`, `damerau_levenshtein`, `levenstein`,
* `jarowinkler`, `ngram`
* @returns {TermSuggester} returns `this` so that calls can be chained.
* @throws {Error} If `implMethod` is not one of `internal`, `damerau_levenshtein`,
* `levenstein`, `jarowinkler` or ngram`.
*/
stringDistance(implMethod) {
if (isNil(implMethod)) invalidStringDistanceParam(implMethod);
const implMethodLower = implMethod.toLowerCase();
if (!STRING_DISTANCE_SET.has(implMethodLower)) {
invalidStringDistanceParam(implMethod);
}
this._suggestOpts.string_distance = implMethodLower;
return this;
}
}
module.exports = TermSuggester;