fix aggregateBy func, fix #498

dist/datasource-zabbix/dataProcessor.js

@@ -65,8 +65,10 @@ System.register(['lodash', './utils', './timeseries'], function (_export, _conte
   function aggregateByWrapper(interval, aggregateFunc, datapoints) {
     // Flatten all points in frame and then just use groupBy()
     var flattenedPoints = _.flatten(datapoints, true);
+    // groupBy_perf works with sorted series only
+    var sortedPoints = ts.sortByTime(flattenedPoints);
     var groupByCallback = aggregationFunctions[aggregateFunc];
-    return groupBy(flattenedPoints, interval, groupByCallback);
+    return groupBy(sortedPoints, interval, groupByCallback);
   }
 
   function aggregateWrapper(groupByCallback, interval, datapoints) {

dist/datasource-zabbix/specs/dataProcessor.spec.js

@@ -0,0 +1,51 @@
+import _ from 'lodash';
+import dataProcessor from '../dataProcessor';
+
+describe('dataProcessor', () => {
+  let ctx = {};
+
+  beforeEach(() => {
+    ctx.datapoints = [
+      [[10, 1500000000000], [2, 1500000001000], [7, 1500000002000], [1, 1500000003000]],
+      [[9, 1500000000000],  [3, 1500000001000], [4, 1500000002000], [8, 1500000003000]],
+    ];
+  });
+
+  describe('When apply groupBy() functions', () => {
+    it('should return series average', () => {
+      let aggregateBy = dataProcessor.metricFunctions['groupBy'];
+      const avg2s = _.map(ctx.datapoints, (dp) => aggregateBy('2s', 'avg', dp));
+      expect(avg2s).toEqual([
+        [[6, 1500000000000], [4, 1500000002000]],
+        [[6, 1500000000000], [6, 1500000002000]],
+      ]);
+
+      const avg10s = _.map(ctx.datapoints, (dp) => aggregateBy('10s', 'avg', dp));
+      expect(avg10s).toEqual([
+        [[5, 1500000000000]],
+        [[6, 1500000000000]],
+      ]);
+
+      // not aligned
+      const dp = [[10, 1500000001000], [2, 1500000002000], [7, 1500000003000], [1, 1500000004000]];
+      expect(aggregateBy('2s', 'avg', dp)).toEqual([
+        [10, 1500000000000], [4.5, 1500000002000], [1, 1500000004000]
+      ]);
+    });
+  });
+
+  describe('When apply aggregateBy() functions', () => {
+    it('should return series average', () => {
+      let aggregateBy = dataProcessor.metricFunctions['aggregateBy'];
+      const avg1s = aggregateBy('1s', 'avg', ctx.datapoints);
+      expect(avg1s).toEqual([
+        [9.5, 1500000000000], [2.5, 1500000001000], [5.5, 1500000002000], [4.5, 1500000003000]
+      ]);
+
+      const avg10s = aggregateBy('10s', 'avg', ctx.datapoints);
+      expect(avg10s).toEqual([
+        [5.5, 1500000000000]
+      ]);
+    });
+  });
+});

dist/datasource-zabbix/timeseries.js

@@ -480,7 +480,8 @@ System.register(['lodash', './utils'], function (_export, _context) {
         MIN: MIN,
         MAX: MAX,
         MEDIAN: MEDIAN,
-        PERCENTIL: PERCENTIL
+        PERCENTIL: PERCENTIL,
+        sortByTime: sortByTime
       };
 
       _export('default', exportedFunctions);

src/datasource-zabbix/dataProcessor.js

@@ -79,9 +79,11 @@ function groupByWrapper(interval, groupFunc, datapoints) {
 
 function aggregateByWrapper(interval, aggregateFunc, datapoints) {
   // Flatten all points in frame and then just use groupBy()
-  var flattenedPoints = _.flatten(datapoints, true);
-  var groupByCallback = aggregationFunctions[aggregateFunc];
-  return groupBy(flattenedPoints, interval, groupByCallback);
+  const flattenedPoints = _.flatten(datapoints, true);
+  // groupBy_perf works with sorted series only
+  const sortedPoints = ts.sortByTime(flattenedPoints);
+  let groupByCallback = aggregationFunctions[aggregateFunc];
+  return groupBy(sortedPoints, interval, groupByCallback);
 }
 
 function aggregateWrapper(groupByCallback, interval, datapoints) {

src/datasource-zabbix/specs/dataProcessor.spec.js

@@ -0,0 +1,51 @@
+import _ from 'lodash';
+import dataProcessor from '../dataProcessor';
+
+describe('dataProcessor', () => {
+  let ctx = {};
+
+  beforeEach(() => {
+    ctx.datapoints = [
+      [[10, 1500000000000], [2, 1500000001000], [7, 1500000002000], [1, 1500000003000]],
+      [[9, 1500000000000],  [3, 1500000001000], [4, 1500000002000], [8, 1500000003000]],
+    ];
+  });
+
+  describe('When apply groupBy() functions', () => {
+    it('should return series average', () => {
+      let aggregateBy = dataProcessor.metricFunctions['groupBy'];
+      const avg2s = _.map(ctx.datapoints, (dp) => aggregateBy('2s', 'avg', dp));
+      expect(avg2s).toEqual([
+        [[6, 1500000000000], [4, 1500000002000]],
+        [[6, 1500000000000], [6, 1500000002000]],
+      ]);
+
+      const avg10s = _.map(ctx.datapoints, (dp) => aggregateBy('10s', 'avg', dp));
+      expect(avg10s).toEqual([
+        [[5, 1500000000000]],
+        [[6, 1500000000000]],
+      ]);
+
+      // not aligned
+      const dp = [[10, 1500000001000], [2, 1500000002000], [7, 1500000003000], [1, 1500000004000]];
+      expect(aggregateBy('2s', 'avg', dp)).toEqual([
+        [10, 1500000000000], [4.5, 1500000002000], [1, 1500000004000]
+      ]);
+    });
+  });
+
+  describe('When apply aggregateBy() functions', () => {
+    it('should return series average', () => {
+      let aggregateBy = dataProcessor.metricFunctions['aggregateBy'];
+      const avg1s = aggregateBy('1s', 'avg', ctx.datapoints);
+      expect(avg1s).toEqual([
+        [9.5, 1500000000000], [2.5, 1500000001000], [5.5, 1500000002000], [4.5, 1500000003000]
+      ]);
+
+      const avg10s = aggregateBy('10s', 'avg', ctx.datapoints);
+      expect(avg10s).toEqual([
+        [5.5, 1500000000000]
+      ]);
+    });
+  });
+});

src/datasource-zabbix/timeseries.js

@@ -488,7 +488,8 @@ const exportedFunctions = {
   MIN,
   MAX,
   MEDIAN,
-  PERCENTIL
+  PERCENTIL,
+  sortByTime
 };
 
 export default exportedFunctions;