move timeseries processing into 'timeseries' module
This commit is contained in:
Alexander Zobnin
248
dist/datasource-zabbix/dataProcessor.js
vendored
248
dist/datasource-zabbix/dataProcessor.js
vendored
@@ -1,118 +1,11 @@
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'use strict';
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System.register(['lodash', './utils'], function (_export, _context) {
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System.register(['lodash', './utils', './timeseries'], function (_export, _context) {
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"use strict";
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var _, utils, metricFunctions, aggregationFunctions;
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var _, utils, ts, downsampleSeries, groupBy, sumSeries, scale, delta, SUM, COUNT, AVERAGE, MIN, MAX, MEDIAN, metricFunctions, aggregationFunctions;
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/**
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* Downsample datapoints series
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*/
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function downsampleSeries(datapoints, time_to, ms_interval, func) {
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var downsampledSeries = [];
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var timeWindow = {
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from: time_to * 1000 - ms_interval,
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to: time_to * 1000
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};
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var points_sum = 0;
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var points_num = 0;
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var value_avg = 0;
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var frame = [];
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for (var i = datapoints.length - 1; i >= 0; i -= 1) {
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if (timeWindow.from < datapoints[i][1] && datapoints[i][1] <= timeWindow.to) {
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points_sum += datapoints[i][0];
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points_num++;
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frame.push(datapoints[i][0]);
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} else {
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value_avg = points_num ? points_sum / points_num : 0;
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if (func === "max") {
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downsampledSeries.push([_.max(frame), timeWindow.to]);
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} else if (func === "min") {
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downsampledSeries.push([_.min(frame), timeWindow.to]);
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}
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// avg by default
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else {
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downsampledSeries.push([value_avg, timeWindow.to]);
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}
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// Shift time window
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timeWindow.to = timeWindow.from;
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timeWindow.from -= ms_interval;
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points_sum = 0;
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points_num = 0;
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frame = [];
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// Process point again
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i++;
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}
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}
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return downsampledSeries.reverse();
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}
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/**
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* Group points by given time interval
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* datapoints: [[<value>, <unixtime>], ...]
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*/
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function groupBy(interval, groupByCallback, datapoints) {
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var ms_interval = utils.parseInterval(interval);
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// Calculate frame timestamps
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var frames = _.groupBy(datapoints, function (point) {
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// Calculate time for group of points
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return Math.floor(point[1] / ms_interval) * ms_interval;
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});
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// frame: { '<unixtime>': [[<value>, <unixtime>], ...] }
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// return [{ '<unixtime>': <value> }, { '<unixtime>': <value> }, ...]
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var grouped = _.mapValues(frames, function (frame) {
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var points = _.map(frame, function (point) {
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return point[0];
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});
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return groupByCallback(points);
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});
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// Convert points to Grafana format
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return sortByTime(_.map(grouped, function (value, timestamp) {
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return [Number(value), Number(timestamp)];
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}));
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}function sumSeries(timeseries) {
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// Calculate new points for interpolation
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var new_timestamps = _.uniq(_.map(_.flatten(timeseries, true), function (point) {
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return point[1];
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}));
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new_timestamps = _.sortBy(new_timestamps);
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var interpolated_timeseries = _.map(timeseries, function (series) {
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var timestamps = _.map(series, function (point) {
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return point[1];
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});
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var new_points = _.map(_.difference(new_timestamps, timestamps), function (timestamp) {
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return [null, timestamp];
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});
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var new_series = series.concat(new_points);
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return sortByTime(new_series);
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});
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_.each(interpolated_timeseries, interpolateSeries);
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var new_timeseries = [];
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var sum;
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for (var i = new_timestamps.length - 1; i >= 0; i--) {
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sum = 0;
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for (var j = interpolated_timeseries.length - 1; j >= 0; j--) {
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sum += interpolated_timeseries[j][i][0];
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}
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new_timeseries.push([sum, new_timestamps[i]]);
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}
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return sortByTime(new_timeseries);
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}function limit(order, n, orderByFunc, timeseries) {
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function limit(order, n, orderByFunc, timeseries) {
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var orderByCallback = aggregationFunctions[orderByFunc];
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var sortByIteratee = function sortByIteratee(ts) {
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var values = _.map(ts.datapoints, function (point) {
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@@ -126,31 +19,14 @@ System.register(['lodash', './utils'], function (_export, _context) {
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} else {
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return sortedTimeseries.slice(-n);
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}
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}function SUM(values) {
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var sum = 0;
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_.each(values, function (value) {
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sum += value;
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});
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return sum;
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}function COUNT(values) {
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return values.length;
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}function AVERAGE(values) {
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var sum = 0;
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_.each(values, function (value) {
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sum += value;
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});
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return sum / values.length;
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}function MIN(values) {
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return _.min(values);
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}function MAX(values) {
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return _.max(values);
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}function MEDIAN(values) {
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var sorted = _.sortBy(values);
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return sorted[Math.floor(sorted.length / 2)];
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}function setAlias(alias, timeseries) {
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}
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function setAlias(alias, timeseries) {
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timeseries.target = alias;
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return timeseries;
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}function replaceAlias(regexp, newAlias, timeseries) {
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}
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function replaceAlias(regexp, newAlias, timeseries) {
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var pattern = void 0;
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if (utils.isRegex(regexp)) {
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pattern = utils.buildRegex(regexp);
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@@ -161,105 +37,71 @@ System.register(['lodash', './utils'], function (_export, _context) {
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var alias = timeseries.target.replace(pattern, newAlias);
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timeseries.target = alias;
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return timeseries;
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}function setAliasByRegex(alias, timeseries) {
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}
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function setAliasByRegex(alias, timeseries) {
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timeseries.target = extractText(timeseries.target, alias);
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return timeseries;
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}function extractText(str, pattern) {
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}
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function extractText(str, pattern) {
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var extractPattern = new RegExp(pattern);
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var extractedValue = extractPattern.exec(str);
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extractedValue = extractedValue[0];
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return extractedValue;
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}function scale(factor, datapoints) {
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return _.map(datapoints, function (point) {
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return [point[0] * factor, point[1]];
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});
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}function delta(datapoints) {
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var newSeries = [];
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var deltaValue = void 0;
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for (var i = 1; i < datapoints.length; i++) {
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deltaValue = datapoints[i][0] - datapoints[i - 1][0];
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newSeries.push([deltaValue, datapoints[i][1]]);
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}
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return newSeries;
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}function groupByWrapper(interval, groupFunc, datapoints) {
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}
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function groupByWrapper(interval, groupFunc, datapoints) {
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var groupByCallback = aggregationFunctions[groupFunc];
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return groupBy(interval, groupByCallback, datapoints);
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}function aggregateByWrapper(interval, aggregateFunc, datapoints) {
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}
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function aggregateByWrapper(interval, aggregateFunc, datapoints) {
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// Flatten all points in frame and then just use groupBy()
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var flattenedPoints = _.flatten(datapoints, true);
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var groupByCallback = aggregationFunctions[aggregateFunc];
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return groupBy(interval, groupByCallback, flattenedPoints);
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}function aggregateWrapper(groupByCallback, interval, datapoints) {
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var flattenedPoints = _.flatten(datapoints, true);
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return groupBy(interval, groupByCallback, flattenedPoints);
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}function sortByTime(series) {
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return _.sortBy(series, function (point) {
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return point[1];
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});
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}
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/**
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* Interpolate series with gaps
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*/
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function interpolateSeries(series) {
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var left, right;
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function aggregateWrapper(groupByCallback, interval, datapoints) {
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var flattenedPoints = _.flatten(datapoints, true);
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return groupBy(interval, groupByCallback, flattenedPoints);
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}
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// Interpolate series
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for (var i = series.length - 1; i >= 0; i--) {
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if (!series[i][0]) {
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left = findNearestLeft(series, series[i]);
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right = findNearestRight(series, series[i]);
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if (!left) {
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left = right;
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}
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if (!right) {
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right = left;
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}
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series[i][0] = linearInterpolation(series[i][1], left, right);
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}
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}
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return series;
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}function linearInterpolation(timestamp, left, right) {
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if (left[1] === right[1]) {
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return (left[0] + right[0]) / 2;
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} else {
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return left[0] + (right[0] - left[0]) / (right[1] - left[1]) * (timestamp - left[1]);
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}
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}function findNearestRight(series, point) {
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var point_index = _.indexOf(series, point);
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var nearestRight;
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for (var i = point_index; i < series.length; i++) {
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if (series[i][0] !== null) {
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return series[i];
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}
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}
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return nearestRight;
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}function findNearestLeft(series, point) {
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var point_index = _.indexOf(series, point);
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var nearestLeft;
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for (var i = point_index; i > 0; i--) {
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if (series[i][0] !== null) {
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return series[i];
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}
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}
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return nearestLeft;
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}function timeShift(interval, range) {
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function timeShift(interval, range) {
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var shift = utils.parseTimeShiftInterval(interval) / 1000;
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return _.map(range, function (time) {
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return time - shift;
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});
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}function unShiftTimeSeries(interval, datapoints) {
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}
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function unShiftTimeSeries(interval, datapoints) {
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var unshift = utils.parseTimeShiftInterval(interval);
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return _.map(datapoints, function (dp) {
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return [dp[0], dp[1] + unshift];
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});
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}return {
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}
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return {
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setters: [function (_lodash) {
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_ = _lodash.default;
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}, function (_utils) {
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utils = _utils;
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}, function (_timeseries) {
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ts = _timeseries.default;
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}],
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execute: function () {
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downsampleSeries = ts.downsample;
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groupBy = ts.groupBy;
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sumSeries = ts.sumSeries;
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scale = ts.scale;
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delta = ts.delta;
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SUM = ts.SUM;
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COUNT = ts.COUNT;
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AVERAGE = ts.AVERAGE;
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MIN = ts.MIN;
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MAX = ts.MAX;
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MEDIAN = ts.MEDIAN;
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metricFunctions = {
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groupBy: groupByWrapper,
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scale: scale,
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