Merge branch 'feature/series-aggregation'

NovatecConsulting · Dec 5, 2018 · d23edb1 · d23edb1
2 parents 6edbcb9 + f94caf0
commit d23edb1
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Showing 3 changed files with 31 additions and 11 deletions.
diff --git a/README.md b/README.md
@@ -49,7 +49,7 @@ You can create variables for templating based on APM queries. You can either que
 Considering the different temporal aggregation levels of CA APM, it makes sense to use a template variable to control the temporal resolution of time series data dynamically. Simply create a dashboard variable of type _Interval_ and use `15s,30s,1m,2m,6m,12m,24m,48m,1h,168m,12h` for the values.
 
 ### Series Aggregation
-In raw query mode, you can choose an aggregation mode to aggregate multiple metrics into a single series of values. This way, you can get a single aggregated time series for visualization in Grafana if your query returns multiple metrics. The implemented aggregation modes are _sum_, _mean_, _max_, _min_, and _median_. Be careful when your metrics might contain null values - these are not explicitly handled by the aggregation methods.
+In raw query mode, you can choose an aggregation mode to aggregate multiple metrics into a single series of values. This way, you can get a single aggregated time series for visualization in Grafana if your query returns multiple metrics. The implemented aggregation modes are _sum_, _mean_, _max_, _min_, and _median_.
 
 ![Series-Aggregation](https://github.com/NovaTecConsulting/ca-apm-grafana-datasource/blob/master/media/multi_series_aggregation.gif)
 

diff --git a/dist/datasource.js b/dist/datasource.js
@@ -164,16 +164,26 @@ var ApmDatasource = /** @class */ (function () {
             if (!(rawMetricDataPoint.childNodes[3].getAttribute("xsi:nil") === "true")) {
                 // we have a value, convert to int implicitly
                 value = +rawMetricDataPoint.childNodes[3].textContent;
+                // collect values into map, drop NaN values
+                if (!isNaN(value)) {
+                    metricData[id] = {
+                        metricKey: rawMetricDataPoint.childNodes[0].textContent + legendSeparator + rawMetricDataPoint.childNodes[1].textContent,
+                        metricValue: value
+                    };
+                }
             }
-            metricData[id] = {
-                metricKey: rawMetricDataPoint.childNodes[0].textContent + legendSeparator + rawMetricDataPoint.childNodes[1].textContent,
-                metricValue: value
-            };
         }
         ;
         // for each time slice, collect all referenced data points
         slices.forEach(function (slice) {
-            var dataPoints = slice.references.map(function (reference) { return metricData[reference]; });
+            var dataPoints = slice.references
+                .reduce(function (dataPoints, reference) {
+                var dataPoint = metricData[reference];
+                if (typeof dataPoint != "undefined") {
+                    dataPoints.push(dataPoint);
+                }
+                return dataPoints;
+            }, []);
             // post processing, aggregation
             if (/^sum|mean|max|min|median$/.test(aggregationMode)) {
                 var aggregate = aggregations[aggregationMode](dataPoints.map(function (dataPoint) { return dataPoint.metricValue; }));

diff --git a/src/datasource.ts b/src/datasource.ts
@@ -188,17 +188,27 @@ export class ApmDatasource {
             if (!(rawMetricDataPoint.childNodes[3].getAttribute("xsi:nil") === "true")) {
                 // we have a value, convert to int implicitly
                 value = +rawMetricDataPoint.childNodes[3].textContent;
-            }
 
-            metricData[id] = {
-                metricKey: rawMetricDataPoint.childNodes[0].textContent + legendSeparator + rawMetricDataPoint.childNodes[1].textContent,
-                metricValue: value
+                // collect values into map, drop NaN values
+                if (!isNaN(value)) {
+                    metricData[id] = {
+                        metricKey: rawMetricDataPoint.childNodes[0].textContent + legendSeparator + rawMetricDataPoint.childNodes[1].textContent,
+                        metricValue: value
+                    }
+                }
             }
         };
 
         // for each time slice, collect all referenced data points
         slices.forEach(function (slice) {
-            var dataPoints: [MetricPoint] = slice.references.map(reference => metricData[reference]);
+            var dataPoints: [MetricPoint] = slice.references
+                .reduce((dataPoints, reference) => {
+                    const dataPoint = metricData[reference];
+                    if (typeof dataPoint != "undefined") {
+                        dataPoints.push(dataPoint);
+                    }
+                    return dataPoints;
+                }, [])
 
             // post processing, aggregation
             if (/^sum|mean|max|min|median$/.test(aggregationMode)) {