@jmaitrehenry/elastic-builder/src/aggregations/metrics-aggregations/percentiles-aggregation.js

A JavaScript implementation of the elasticsearch Query DSL

'use strict';

const {
    util: { checkType }
} = require('../../core');

const MetricsAggregationBase = require('./metrics-aggregation-base');

/**
 * A multi-value metrics aggregation that calculates one or more percentiles
 * over numeric values extracted from the aggregated documents. These values can
 * be extracted either from specific numeric fields in the documents, or be
 * generated by a provided script.
 *
 * [Elasticsearch reference](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-metrics-percentile-aggregation.html)
 *
 * Aggregation that calculates one or more percentiles over numeric values
 * extracted from the aggregated documents.
 *
 * @example
 * const agg = esb.percentilesAggregation('load_time_outlier', 'load_time');
 *
 * @example
 * // Convert load time from mills to seconds on-the-fly using script
 * const agg = esb.percentilesAggregation('load_time_outlier').script(
 *     esb.script('inline', "doc['load_time'].value / params.timeUnit")
 *         .lang('painless')
 *         .params({ timeUnit: 1000 })
 * );
 *
 * @param {string} name The name which will be used to refer to this aggregation.
 * @param {string=} field The field to aggregate on
 *
 * @extends MetricsAggregationBase
 */
class PercentilesAggregation extends MetricsAggregationBase {
    // eslint-disable-next-line require-jsdoc
    constructor(name, field) {
        super(name, 'percentiles', field);
    }

    /**
     * Enable the response to be returned as a keyed object where the key is the
     * bucket interval.
     *
     * @example
     * // Return the ranges as an array rather than a hash
     * const agg = esb.percentilesAggregation('balance_outlier', 'balance').keyed(
     *     false
     * );
     *
     * @param {boolean} keyed To enable keyed response or not. True by default
     * @returns {PercentilesAggregation} returns `this` so that calls can be chained
     */
    keyed(keyed) {
        this._aggsDef.keyed = keyed;
        return this;
    }

    /**
     * Specifies the percents of interest.
     * Requested percentiles must be a value between 0-100 inclusive
     *
     * @example
     * // Specify particular percentiles to calculate
     * const agg = esb.percentilesAggregation(
     *     'load_time_outlier',
     *     'load_time'
     * ).percents([95, 99, 99.9]);
     *
     * @param {Array<number>} percents Parameter to specify particular percentiles to calculate
     * @returns {PercentilesAggregation} returns `this` so that calls can be chained
     * @throws {TypeError} If `percents` is not an instance of Array
     */
    percents(percents) {
        checkType(percents, Array);
        this._aggsDef.percents = percents;
        return this;
    }

    /**
     * Compression controls memory usage and approximation error. The compression
     * value limits the maximum number of nodes to 100 * compression. By
     * increasing the compression value, you can increase the accuracy of your
     * percentiles at the cost of more memory. Larger compression values also make
     * the algorithm slower since the underlying tree data structure grows in
     * size, resulting in more expensive operations. The default compression
     * value is 100.
     *
     * @example
     * const agg = esb.percentilesAggregation(
     *     'load_time_outlier',
     *     'load_time'
     * ).tdigest(200);
     *
     * @param {number} compression Parameter to balance memory utilization with estimation accuracy.
     * @returns {PercentilesAggregation} returns `this` so that calls can be chained
     */
    tdigest(compression) {
        this._aggsDef.tdigest = { compression };
        return this;
    }

    /**
     * Compression controls memory usage and approximation error. The compression
     * value limits the maximum number of nodes to 100 * compression. By
     * increasing the compression value, you can increase the accuracy of your
     * percentiles at the cost of more memory. Larger compression values also make
     * the algorithm slower since the underlying tree data structure grows in
     * size, resulting in more expensive operations. The default compression
     * value is 100.
     *
     * Alias for `tdigest`
     *
     * @example
     * const agg = esb.percentilesAggregation(
     *     'load_time_outlier',
     *     'load_time'
     * ).compression(200);
     *
     * @param {number} compression Parameter to balance memory utilization with estimation accuracy.
     * @returns {PercentilesAggregation} returns `this` so that calls can be chained
     */
    compression(compression) {
        this._aggsDef.tdigest = { compression };
        return this;
    }

    /**
     * HDR Histogram (High Dynamic Range Histogram) is an alternative implementation
     * that can be useful when calculating percentiles for latency measurements
     * as it can be faster than the t-digest implementation
     * with the trade-off of a larger memory footprint.
     *
     * The HDR Histogram can be used by specifying the method parameter in the request.
     *
     * @example
     * const agg = esb.percentilesAggregation('load_time_outlier', 'load_time')
     *     .percents([95, 99, 99.9])
     *     .hdr(3);
     *
     * @param {number} numberOfSigDigits The resolution of values
     * for the histogram in number of significant digits
     * @returns {PercentilesAggregation} returns `this` so that calls can be chained
     */
    hdr(numberOfSigDigits) {
        this._aggsDef.hdr = {
            number_of_significant_value_digits: numberOfSigDigits
        };
        return this;
    }
}

module.exports = PercentilesAggregation;