import _ from 'lodash'; // Available in 7.0 // import { getTemplateSrv } from '@grafana/runtime'; import * as utils from './utils'; import ts, { groupBy_perf as groupBy } from './timeseries'; const SUM = ts.SUM; const COUNT = ts.COUNT; const AVERAGE = ts.AVERAGE; const MIN = ts.MIN; const MAX = ts.MAX; const MEDIAN = ts.MEDIAN; const PERCENTILE = ts.PERCENTILE; const downsampleSeries = ts.downsample; const groupBy_exported = (interval, groupFunc, datapoints) => groupBy(datapoints, interval, groupFunc); const sumSeries = ts.sumSeries; const delta = ts.delta; const rate = ts.rate; const scale = (factor, datapoints) => ts.scale_perf(datapoints, factor); const offset = (delta, datapoints) => ts.offset(datapoints, delta); const simpleMovingAverage = (n, datapoints) => ts.simpleMovingAverage(datapoints, n); const expMovingAverage = (a, datapoints) => ts.expMovingAverage(datapoints, a); const percentile = (interval, n, datapoints) => groupBy(datapoints, interval, _.partial(PERCENTILE, n)); function limit(order, n, orderByFunc, timeseries) { const orderByCallback = aggregationFunctions[orderByFunc]; const sortByIteratee = (ts) => { const values = _.map(ts.datapoints, (point) => { return point[0]; }); return orderByCallback(values); }; const sortedTimeseries = _.sortBy(timeseries, sortByIteratee); if (order === 'bottom') { return sortedTimeseries.slice(0, n); } else { return sortedTimeseries.slice(-n); } } function removeAboveValue(n, datapoints) { return _.map(datapoints, point => { return [ (point[0] > n) ? null : point[0], point[1] ]; }); } function removeBelowValue(n, datapoints) { return _.map(datapoints, point => { return [ (point[0] < n) ? null : point[0], point[1] ]; }); } function transformNull(n, datapoints) { return _.map(datapoints, point => { return [ (point[0] !== null) ? point[0] : n, point[1] ]; }); } function sortSeries(direction, timeseries: any[]) { return _.orderBy(timeseries, [ts => { return ts.target.toLowerCase(); }], direction); } function setAlias(alias, timeseries) { // TODO: use getTemplateSrv() when available (since 7.0) if (this.templateSrv && timeseries && timeseries.scopedVars) { alias = this.templateSrv.replace(alias, timeseries.scopedVars); } timeseries.target = alias; return timeseries; } function replaceAlias(regexp, newAlias, timeseries) { let pattern; if (utils.isRegex(regexp)) { pattern = utils.buildRegex(regexp); } else { pattern = regexp; } let alias = timeseries.target.replace(pattern, newAlias); // TODO: use getTemplateSrv() when available (since 7.0) if (this.templateSrv && timeseries && timeseries.scopedVars) { alias = this.templateSrv.replace(alias, timeseries.scopedVars); } timeseries.target = alias; return timeseries; } function setAliasByRegex(alias, timeseries) { timeseries.target = extractText(timeseries.target, alias); return timeseries; } function extractText(str, pattern) { const extractPattern = new RegExp(pattern); const extractedValue = extractPattern.exec(str); return extractedValue[0]; } function groupByWrapper(interval, groupFunc, datapoints) { const groupByCallback = aggregationFunctions[groupFunc]; return groupBy(datapoints, interval, groupByCallback); } function aggregateByWrapper(interval, aggregateFunc, datapoints) { // Flatten all points in frame and then just use groupBy() const flattenedPoints = ts.flattenDatapoints(datapoints); // groupBy_perf works with sorted series only const sortedPoints = ts.sortByTime(flattenedPoints); const groupByCallback = aggregationFunctions[aggregateFunc]; return groupBy(sortedPoints, interval, groupByCallback); } function aggregateWrapper(groupByCallback, interval, datapoints) { const flattenedPoints = ts.flattenDatapoints(datapoints); // groupBy_perf works with sorted series only const sortedPoints = ts.sortByTime(flattenedPoints); return groupBy(sortedPoints, interval, groupByCallback); } function percentileAgg(interval, n, datapoints) { const flattenedPoints = ts.flattenDatapoints(datapoints); // groupBy_perf works with sorted series only const sortedPoints = ts.sortByTime(flattenedPoints); const groupByCallback = _.partial(PERCENTILE, n); return groupBy(sortedPoints, interval, groupByCallback); } function timeShift(interval, range) { const shift = utils.parseTimeShiftInterval(interval) / 1000; return _.map(range, time => { return time - shift; }); } function unShiftTimeSeries(interval, datapoints) { const unshift = utils.parseTimeShiftInterval(interval); return _.map(datapoints, dp => { return [ dp[0], dp[1] + unshift ]; }); } const metricFunctions = { groupBy: groupByWrapper, scale: scale, offset: offset, delta: delta, rate: rate, movingAverage: simpleMovingAverage, exponentialMovingAverage: expMovingAverage, percentile: percentile, transformNull: transformNull, aggregateBy: aggregateByWrapper, // Predefined aggs percentileAgg: percentileAgg, average: _.partial(aggregateWrapper, AVERAGE), min: _.partial(aggregateWrapper, MIN), max: _.partial(aggregateWrapper, MAX), median: _.partial(aggregateWrapper, MEDIAN), sum: _.partial(aggregateWrapper, SUM), count: _.partial(aggregateWrapper, COUNT), sumSeries: sumSeries, removeAboveValue: removeAboveValue, removeBelowValue: removeBelowValue, top: _.partial(limit, 'top'), bottom: _.partial(limit, 'bottom'), sortSeries: sortSeries, timeShift: timeShift, setAlias: setAlias, setAliasByRegex: setAliasByRegex, replaceAlias: replaceAlias }; const aggregationFunctions = { avg: AVERAGE, min: MIN, max: MAX, median: MEDIAN, sum: SUM, count: COUNT }; export default { downsampleSeries: downsampleSeries, groupBy: groupBy_exported, AVERAGE: AVERAGE, MIN: MIN, MAX: MAX, MEDIAN: MEDIAN, SUM: SUM, COUNT: COUNT, unShiftTimeSeries: unShiftTimeSeries, get aggregationFunctions() { return aggregationFunctions; }, get metricFunctions() { return metricFunctions; } };