Examples with Summarizable com.yammer.metrics.core.Summarizable used on opensource projects

Example 1 with Summarizable

use of com.yammer.metrics.core.Summarizable in project java by wavefrontHQ.

the class FlushProcessor method processHistogram.

@Override
public void processHistogram(MetricName name, Histogram histogram, FlushProcessorContext context) {
    if (histogram instanceof WavefrontHistogram) {
        WavefrontHistogram wavefrontHistogram = (WavefrontHistogram) histogram;
        if (useWavefrontHistograms) {
            // export Wavefront histograms in its native format
            if (wavefrontHistogram.count() == 0)
                return;
            for (WavefrontHistogram.MinuteBin bin : wavefrontHistogram.bins(true)) {
                if (bin.getDist().size() == 0)
                    continue;
                int size = bin.getDist().centroids().size();
                List<Double> centroids = new ArrayList<>(size);
                List<Integer> counts = new ArrayList<>(size);
                for (Centroid centroid : bin.getDist().centroids()) {
                    centroids.add(centroid.mean());
                    counts.add(centroid.count());
                }
                context.report(wavefront.report.Histogram.newBuilder().setDuration(// minute bins
                60_000).setType(HistogramType.TDIGEST).setBins(centroids).setCounts(counts).build(), bin.getMinMillis());
                histogramCounter.inc();
            }
        } else {
            // convert Wavefront histogram to Yammer-style histogram
            TDigest tDigest = new AVLTreeDigest(100);
            List<WavefrontHistogram.MinuteBin> bins = wavefrontHistogram.bins(true);
            bins.stream().map(WavefrontHistogram.MinuteBin::getDist).forEach(tDigest::add);
            context.reportSubMetric(tDigest.centroids().stream().mapToLong(Centroid::count).sum(), "count");
            Summarizable summarizable = new Summarizable() {

                @Override
                public double max() {
                    return tDigest.centroids().stream().map(Centroid::mean).max(Comparator.naturalOrder()).orElse(Double.NaN);
                }

                @Override
                public double min() {
                    return tDigest.centroids().stream().map(Centroid::mean).min(Comparator.naturalOrder()).orElse(Double.NaN);
                }

                @Override
                public double mean() {
                    Centroid mean = tDigest.centroids().stream().reduce((x, y) -> new Centroid(x.mean() + (y.mean() * y.count()), x.count() + y.count())).orElse(null);
                    return mean == null || tDigest.centroids().size() == 0 ? Double.NaN : mean.mean() / mean.count();
                }

                @Override
                public double stdDev() {
                    return Double.NaN;
                }

                @Override
                public double sum() {
                    return Double.NaN;
                }
            };
            for (Map.Entry<String, Double> entry : MetricsToTimeseries.explodeSummarizable(summarizable, reportEmptyHistogramStats).entrySet()) {
                if (!entry.getValue().isNaN()) {
                    context.reportSubMetric(entry.getValue(), entry.getKey());
                }
            }
            Sampling sampling = () -> new Snapshot(new double[0]) {

                @Override
                public double get75thPercentile() {
                    return tDigest.quantile(.75);
                }

                @Override
                public double get95thPercentile() {
                    return tDigest.quantile(.95);
                }

                @Override
                public double get98thPercentile() {
                    return tDigest.quantile(.98);
                }

                @Override
                public double get999thPercentile() {
                    return tDigest.quantile(.999);
                }

                @Override
                public double get99thPercentile() {
                    return tDigest.quantile(.99);
                }

                @Override
                public double getMedian() {
                    return tDigest.quantile(.50);
                }

                @Override
                public double getValue(double quantile) {
                    return tDigest.quantile(quantile);
                }

                @Override
                public double[] getValues() {
                    return new double[0];
                }

                @Override
                public int size() {
                    return (int) tDigest.size();
                }
            };
            for (Map.Entry<String, Double> entry : MetricsToTimeseries.explodeSampling(sampling, reportEmptyHistogramStats).entrySet()) {
                if (!entry.getValue().isNaN()) {
                    context.reportSubMetric(entry.getValue(), entry.getKey());
                }
            }
            sentCounter.inc();
        }
    } else {
        context.reportSubMetric(histogram.count(), "count");
        for (Map.Entry<String, Double> entry : MetricsToTimeseries.explodeSummarizable(histogram, reportEmptyHistogramStats).entrySet()) {
            if (!entry.getValue().isNaN()) {
                context.reportSubMetric(entry.getValue(), entry.getKey());
            }
        }
        for (Map.Entry<String, Double> entry : MetricsToTimeseries.explodeSampling(histogram, reportEmptyHistogramStats).entrySet()) {
            if (!entry.getValue().isNaN()) {
                context.reportSubMetric(entry.getValue(), entry.getKey());
            }
        }
        sentCounter.inc();
        histogram.clear();
    }
}