// ------------------------------------------------------------------- // // // This file is provided to you under the Apache License, // Version 2.0 (the "License"); you may not use this file // except in compliance with the License. You may obtain // a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, // software distributed under the License is distributed on an // "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY // KIND, either express or implied. See the License for the // specific language governing permissions and limitations // under the License. // // ------------------------------------------------------------------- // // This file contains Javascript MapReduce functions copied from the // "Riak Function Contrib" project. // Riak.Contrib = { // Count keys in a group of results. // http://contrib.basho.com/count_keys.html mapCount: function(){ return [1]; }, // Generate commonly used statistics from an array of numbers. // Supports count, sum, min, max, percentiles, mean, variance, and // stddev. // http://contrib.basho.com/stats.html reduceStats: function(data) { var result = {}; data.sort(function(a,b){return a-b;}); result.count = data.length; // Since the data is sorted, the minimum value // is at the beginning of the array, the median // value is in the middle of the array, and the // maximum value is at the end of the array. result.min = data[0]; result.max = data[data.length - 1]; var ntileFunc = function(percentile){ if (data.length == 1) return data[0]; var ntileRank = ((percentile/100) * (data.length - 1)) + 1; var integralRank = Math.floor(ntileRank); var fractionalRank = ntileRank - integralRank; var lowerValue = data[integralRank-1]; var upperValue = data[integralRank]; return (fractionalRank * (upperValue - lowerValue)) + lowerValue; }; result.percentile25 = ntileFunc(25); result.median = ntileFunc(50); result.percentile75 = ntileFunc(75); result.percentile99 = ntileFunc(99); // Compute the mean and variance using a // numerically stable algorithm. var sqsum = 0; result.mean = data[0]; result.sum = result.mean * result.count; for (var i = 1; i < data.length; ++i) { var x = data[i]; var delta = x - result.mean; var sweep = i + 1.0; result.mean += delta / sweep; sqsum += delta * delta * (i / sweep); result.sum += x; } result.variance = sqsum / result.count; result.sdev = Math.sqrt(result.variance); return result; } };