Implement groupBy with for() and measure performance

about 8 times faster

src/datasource-zabbix/benchmarks/timeseries_bench.js

@@ -31,5 +31,16 @@ module.exports = [
         ts.sumSeries(prepeared_series);
       }
     }
+  },
+  {
+    name: 'groupBy vs groupBy_perf',
+    tests: {
+      'groupBy()': () => {
+        ts.groupBy(datapoints, '5m', ts.AVERAGE);
+      },
+      'groupBy_perf()': () => {
+        ts.groupBy_perf(datapoints, '5m', ts.AVERAGE);
+      }
+    }
   }
 ];

src/datasource-zabbix/dataProcessor.js

@@ -3,7 +3,7 @@ import * as utils from './utils';
 import ts from './timeseries';
 
 let downsampleSeries = ts.downsample;
-let groupBy = ts.groupBy;
+let groupBy = ts.groupBy_perf;
 let sumSeries = ts.sumSeries;
 let delta = ts.delta;
 let scale = (factor, datapoints) => ts.scale(datapoints, factor);

src/datasource-zabbix/timeseries.js

@@ -11,6 +11,9 @@
 import _ from 'lodash';
 import * as utils from './utils';
 
+const POINT_VALUE = 0;
+const POINT_TIMESTAMP = 1;
+
 /**
  * Downsample time series by using given function (avg, min, max).
  */
@@ -90,6 +93,34 @@ function groupBy(datapoints, interval, groupByCallback) {
   }));
 }
 
+function groupBy_perf(datapoints, interval, groupByCallback) {
+  let ms_interval = utils.parseInterval(interval);
+  let grouped_series = [];
+  let frame_values = [];
+  let frame_value;
+  let frame_ts = datapoints.length ? getPointTimeFrame(datapoints[0][POINT_TIMESTAMP], ms_interval) : 0;
+  let point_frame_ts = frame_ts;
+  let point;
+
+  for (let i=0; i < datapoints.length; i++) {
+    point = datapoints[i];
+    point_frame_ts = getPointTimeFrame(point[POINT_TIMESTAMP], ms_interval);
+    if (point_frame_ts === frame_ts) {
+      frame_values.push(point[POINT_VALUE]);
+    } else {
+      frame_value = groupByCallback(frame_values);
+      grouped_series.push([frame_value, frame_ts]);
+      frame_ts = point_frame_ts;
+      frame_values = [point[POINT_VALUE]];
+    }
+  }
+
+  frame_value = groupByCallback(frame_values);
+  grouped_series.push([frame_value, frame_ts]);
+
+  return grouped_series;
+}
+
 /**
  * Summarize set of time series into one.
  * @param {datapoints[]} timeseries array of time series
@@ -184,6 +215,18 @@ function MEDIAN(values) {
 // Utility functions //
 ///////////////////////
 
+/**
+ * For given point calculate corresponding time frame.
+ *
+ * |__*_|_*__|___*| -> |*___|*___|*___|
+ *
+ * @param {*} timestamp
+ * @param {*} ms_interval
+ */
+function getPointTimeFrame(timestamp, ms_interval) {
+  return Math.floor(timestamp / ms_interval) * ms_interval;
+}
+
 function sortByTime(series) {
   return _.sortBy(series, function (point) {
     return point[1];
@@ -250,6 +293,7 @@ function findNearestLeft(series, point) {
 const exportedFunctions = {
   downsample,
   groupBy,
+  groupBy_perf,
   sumSeries,
   scale,
   delta,