feat: Add rank_feature query (#194)

Rank feature query was added in Elasticsearch v7.0.

src/index.d.ts

@@ -3268,6 +3268,86 @@ declare namespace esb {
      */
     export function distanceFeatureQuery(field?: string): DistanceFeatureQuery;
 
+    /**
+     * The `rank_feature` query boosts the relevance score on the numeric value of
+     * document with a rank_feature/rank_features field.
+     *
+     * [Elasticsearch reference](https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-rank-feature-query.html)
+     *
+     * NOTE: This query was added in elasticsearch v7.0.
+     *
+     * @example
+     * const query = new RankFeatureQuery('rank_feature_field');
+     *   query
+     *       .linear()
+     *       .toJSON();
+     * @param {string} field The field inside the document to be used in the query
+     * @return {RankFeatureQuery}
+     */
+    export class RankFeatureQuery extends Query {
+        constructor(field?: string);
+
+        /**
+         * Sets the field for the `distance_feature` query
+         * @param {string} fieldName Name of the field inside the document
+         * @returns {DistanceFeatureQuery} Instance of the query
+         */
+        field(fieldName: string): RankFeatureQuery;
+
+        /**
+         * Linear function to boost relevance scores based on the value of the rank feature field
+         * @returns {RankFeatureQuery}
+         */
+        linear() : RankFeatureQuery;
+
+        /**
+         * Saturation function to boost relevance scores based on the value of the rank feature field.
+         * Uses a default pivot value computed by Elasticsearch.
+         * @returns {RankFeatureQuery}
+         */
+        saturation() : RankFeatureQuery;
+
+        /**
+         * Saturation function to boost relevance scores based on the value of the rank feature field.
+         * @param {number} pivot
+         * @returns {RankFeatureQuery}
+         */
+        saturationPivot(pivot : number) : RankFeatureQuery;
+
+        /**
+         * The log function gives a score equal to log(scaling_factor + S), where S
+         * is the value of the rank feature field and scaling_factor is a configurable
+         * scaling factor.
+         * @param {number} scaling_factor
+         * @returns {RankFeatureQuery}
+         */
+        log(scalingFactor : number) : RankFeatureQuery;
+
+        /**
+         * The sigmoid function extends the saturation function with a configurable exponent.
+         * @param {number} pivot
+         * @param {number} exponent
+         * @returns {RankFeatureQuery}
+         */
+        sigmoid(pivot : number, exponent : number) : RankFeatureQuery
+    }
+
+    /**
+     * The `rank_feature` query boosts the relevance score on the numeric value of
+     * document with a rank_feature/rank_features field.
+     *
+     * [Elasticsearch reference](https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-rank-feature-query.html)
+     *
+     * @example
+     * const query = new RankFeatureQuery('rank_feature_field');
+     *   query
+     *       .linear()
+     *       .toJSON();
+     * @param {string} field The field inside the document to be used in the query
+     * @return {RankFeatureQuery}
+     */
+    export function rankFeatureQuery(field?: string): RankFeatureQuery;
+
     /**
      * Interface-like class used to group and identify various implementations of Span queries.
      *

src/index.js

@@ -73,7 +73,8 @@ const {
         ScriptQuery,
         ScriptScoreQuery,
         PercolateQuery,
-        DistanceFeatureQuery
+        DistanceFeatureQuery,
+        RankFeatureQuery
     },
     spanQueries: {
         SpanTermQuery,
@@ -304,6 +305,9 @@ exports.percolateQuery = constructorWrapper(PercolateQuery);
 exports.DistanceFeatureQuery = DistanceFeatureQuery;
 exports.distanceFeatureQuery = constructorWrapper(DistanceFeatureQuery);
 
+exports.RankFeatureQuery = RankFeatureQuery;
+exports.rankFeatureQuery = constructorWrapper(RankFeatureQuery);
+
 /* ============ ============ ============ */
 /* ============ Span Queries ============ */
 /* ============ ============ ============ */

src/queries/specialized-queries/index.js

@@ -5,3 +5,4 @@ exports.ScriptQuery = require('./script-query');
 exports.ScriptScoreQuery = require('./script-score-query');
 exports.PercolateQuery = require('./percolate-query');
 exports.DistanceFeatureQuery = require('./distance-feature-query');
+exports.RankFeatureQuery = require('./rank-feature-query');

src/queries/specialized-queries/rank-feature-query.js

@@ -0,0 +1,98 @@
+'use strict';
+
+const { Query } = require('../../core');
+const isNil = require('lodash.isnil');
+
+/**
+ * The rank_feature query boosts the relevance score on the numeric value of
+ * document with a rank_feature/rank_features field.
+ *
+ * [Elasticsearch reference](https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-rank-feature-query.html)
+ *
+ * NOTE: This query was added in elasticsearch v7.0.
+ *
+ * @example
+ * const query = new RankFeatureQuery('rank_feature_field');
+ *   query
+ *       .linear()
+ *       .toJSON();
+ * @param {string} field The field inside the document to be used in the query
+ * @extends Query
+ */
+class RankFeatureQuery extends Query {
+    /**
+     * @param {string} field The field inside the document to be used in the query
+     */
+    constructor(field) {
+        super('rank_feature');
+        if (!isNil(field)) this._queryOpts.field = field;
+    }
+
+    /**
+     * Sets the field for the `rank_feature` query
+     * @param {string} fieldName Name of the field inside the document
+     * @returns {RankFeatureQuery} Instance of the distance feature query
+     */
+    field(fieldName) {
+        this._queryOpts.field = fieldName;
+        return this;
+    }
+
+    /**
+     * Linear function to boost relevance scores based on the value of the rank feature field
+     * @returns {RankFeatureQuery}
+     */
+    linear() {
+        this._queryOpts.linear = {};
+        return this;
+    }
+
+    /**
+     * Saturation function to boost relevance scores based on the value of the rank feature field.
+     * Uses a default pivot value computed by Elasticsearch.
+     * @returns {RankFeatureQuery}
+     */
+    saturation() {
+        this._queryOpts.saturation = {};
+        return this;
+    }
+
+    /**
+     * Saturation function to boost relevance scores based on the value of the rank feature field.
+     * @param {number} pivot
+     * @returns {RankFeatureQuery}
+     */
+    saturationPivot(pivot) {
+        this._queryOpts.saturation = {};
+        this._queryOpts.saturation.pivot = pivot;
+        return this;
+    }
+
+    /**
+     * The log function gives a score equal to log(scaling_factor + S), where S
+     * is the value of the rank feature field and scaling_factor is a configurable
+     * scaling factor.
+     * @param {number} scaling_factor
+     * @returns {RankFeatureQuery}
+     */
+    log(scalingFactor) {
+        this._queryOpts.log = {};
+        this._queryOpts.log.scaling_factor = scalingFactor;
+        return this;
+    }
+
+    /**
+     * The sigmoid function extends the saturation function with a configurable exponent.
+     * @param {number} pivot
+     * @param {number} exponent
+     * @returns {RankFeatureQuery}
+     */
+    sigmoid(pivot, exponent) {
+        this._queryOpts.sigmoid = {};
+        this._queryOpts.sigmoid.pivot = pivot;
+        this._queryOpts.sigmoid.exponent = exponent;
+        return this;
+    }
+}
+
+module.exports = RankFeatureQuery;

test/queries-test/rank-feature.test.js

@@ -0,0 +1,86 @@
+import test from 'ava';
+import { RankFeatureQuery } from '../../src';
+
+test('Should test no args rank feature query', t => {
+    const value = new RankFeatureQuery('my_field').toJSON();
+    const expected = {
+        rank_feature: {
+            field: 'my_field'
+        }
+    };
+    t.deepEqual(value, expected);
+});
+
+test('Should test with fieldName', t => {
+    const value = new RankFeatureQuery().field('my_field').toJSON();
+    const expected = {
+        rank_feature: {
+            field: 'my_field'
+        }
+    };
+    t.deepEqual(value, expected);
+});
+
+test('Should test linear rank feature query', t => {
+    const value = new RankFeatureQuery('my_field').linear().toJSON();
+    const expected = {
+        rank_feature: {
+            field: 'my_field',
+            linear: {}
+        }
+    };
+    t.deepEqual(value, expected);
+});
+
+test('Should test saturation rank feature query', t => {
+    const value = new RankFeatureQuery('my_field').saturation().toJSON();
+    const expected = {
+        rank_feature: {
+            field: 'my_field',
+            saturation: {}
+        }
+    };
+    t.deepEqual(value, expected);
+});
+
+test('Should test saturation with pivot rank feature query', t => {
+    const value = new RankFeatureQuery('my_field')
+        .saturationPivot(123)
+        .toJSON();
+    const expected = {
+        rank_feature: {
+            field: 'my_field',
+            saturation: {
+                pivot: 123
+            }
+        }
+    };
+    t.deepEqual(value, expected);
+});
+
+test('Should test sigmoid rank feature query', t => {
+    const value = new RankFeatureQuery('my_field').sigmoid(2, 0.6).toJSON();
+    const expected = {
+        rank_feature: {
+            field: 'my_field',
+            sigmoid: {
+                pivot: 2,
+                exponent: 0.6
+            }
+        }
+    };
+    t.deepEqual(value, expected);
+});
+
+test('Should test logarithmic rank feature query', t => {
+    const value = new RankFeatureQuery('my_field').log(2).toJSON();
+    const expected = {
+        rank_feature: {
+            field: 'my_field',
+            log: {
+                scaling_factor: 2
+            }
+        }
+    };
+    t.deepEqual(value, expected);
+});