Examples with Percentiles org.apache.kafka.common.metrics.stats.Percentiles used on opensource projects

Example 1 with Percentiles

use of org.apache.kafka.common.metrics.stats.Percentiles in project kafka by apache.

the class MetricsTest method testSimpleStats.

@Test
public void testSimpleStats() throws Exception {
    ConstantMeasurable measurable = new ConstantMeasurable();
    metrics.addMetric(metrics.metricName("direct.measurable", "grp1", "The fraction of time an appender waits for space allocation."), measurable);
    Sensor s = metrics.sensor("test.sensor");
    s.add(metrics.metricName("test.avg", "grp1"), new Avg());
    s.add(metrics.metricName("test.max", "grp1"), new Max());
    s.add(metrics.metricName("test.min", "grp1"), new Min());
    s.add(metrics.metricName("test.rate", "grp1"), new Rate(TimeUnit.SECONDS));
    s.add(metrics.metricName("test.occurences", "grp1"), new Rate(TimeUnit.SECONDS, new Count()));
    s.add(metrics.metricName("test.count", "grp1"), new Count());
    s.add(new Percentiles(100, -100, 100, BucketSizing.CONSTANT, new Percentile(metrics.metricName("test.median", "grp1"), 50.0), new Percentile(metrics.metricName("test.perc99_9", "grp1"), 99.9)));
    Sensor s2 = metrics.sensor("test.sensor2");
    s2.add(metrics.metricName("s2.total", "grp1"), new Total());
    s2.record(5.0);
    int sum = 0;
    int count = 10;
    for (int i = 0; i < count; i++) {
        s.record(i);
        sum += i;
    }
    // prior to any time passing
    double elapsedSecs = (config.timeWindowMs() * (config.samples() - 1)) / 1000.0;
    assertEquals(String.format("Occurrences(0...%d) = %f", count, count / elapsedSecs), count / elapsedSecs, metrics.metrics().get(metrics.metricName("test.occurences", "grp1")).value(), EPS);
    // pretend 2 seconds passed...
    long sleepTimeMs = 2;
    time.sleep(sleepTimeMs * 1000);
    elapsedSecs += sleepTimeMs;
    assertEquals("s2 reflects the constant value", 5.0, metrics.metrics().get(metrics.metricName("s2.total", "grp1")).value(), EPS);
    assertEquals("Avg(0...9) = 4.5", 4.5, metrics.metrics().get(metrics.metricName("test.avg", "grp1")).value(), EPS);
    assertEquals("Max(0...9) = 9", count - 1, metrics.metrics().get(metrics.metricName("test.max", "grp1")).value(), EPS);
    assertEquals("Min(0...9) = 0", 0.0, metrics.metrics().get(metrics.metricName("test.min", "grp1")).value(), EPS);
    assertEquals("Rate(0...9) = 1.40625", sum / elapsedSecs, metrics.metrics().get(metrics.metricName("test.rate", "grp1")).value(), EPS);
    assertEquals(String.format("Occurrences(0...%d) = %f", count, count / elapsedSecs), count / elapsedSecs, metrics.metrics().get(metrics.metricName("test.occurences", "grp1")).value(), EPS);
    assertEquals("Count(0...9) = 10", (double) count, metrics.metrics().get(metrics.metricName("test.count", "grp1")).value(), EPS);
}

Example 2 with Percentiles

use of org.apache.kafka.common.metrics.stats.Percentiles in project apache-kafka-on-k8s by banzaicloud.

the class MetricsBench method main.

public static void main(String[] args) {
    long iters = Long.parseLong(args[0]);
    Metrics metrics = new Metrics();
    try {
        Sensor parent = metrics.sensor("parent");
        Sensor child = metrics.sensor("child", parent);
        for (Sensor sensor : Arrays.asList(parent, child)) {
            sensor.add(metrics.metricName(sensor.name() + ".avg", "grp1"), new Avg());
            sensor.add(metrics.metricName(sensor.name() + ".count", "grp1"), new Count());
            sensor.add(metrics.metricName(sensor.name() + ".max", "grp1"), new Max());
            sensor.add(new Percentiles(1024, 0.0, iters, BucketSizing.CONSTANT, new Percentile(metrics.metricName(sensor.name() + ".median", "grp1"), 50.0), new Percentile(metrics.metricName(sensor.name() + ".p_99", "grp1"), 99.0)));
        }
        long start = System.nanoTime();
        for (int i = 0; i < iters; i++) parent.record(i);
        double ellapsed = (System.nanoTime() - start) / (double) iters;
        System.out.println(String.format("%.2f ns per metric recording.", ellapsed));
    } finally {
        metrics.close();
    }
}

Example 3 with Percentiles

use of org.apache.kafka.common.metrics.stats.Percentiles in project kafka by apache.

the class MetricsTest method shouldPinSmallerValuesToMin.

@Test
public void shouldPinSmallerValuesToMin() {
    final double min = 0.0d;
    final double max = 100d;
    Percentiles percs = new Percentiles(1000, min, max, BucketSizing.LINEAR, new Percentile(metrics.metricName("test.p50", "grp1"), 50));
    MetricConfig config = new MetricConfig().eventWindow(50).samples(2);
    Sensor sensor = metrics.sensor("test", config);
    sensor.add(percs);
    Metric p50 = this.metrics.metrics().get(metrics.metricName("test.p50", "grp1"));
    sensor.record(min - 100);
    sensor.record(min - 100);
    assertEquals(min, (double) p50.metricValue(), 0d);
}

Example 4 with Percentiles

use of org.apache.kafka.common.metrics.stats.Percentiles in project kafka by apache.

the class MetricsTest method verifyStats.

private void verifyStats(Function<KafkaMetric, Double> metricValueFunc) {
    ConstantMeasurable measurable = new ConstantMeasurable();
    metrics.addMetric(metrics.metricName("direct.measurable", "grp1", "The fraction of time an appender waits for space allocation."), measurable);
    Sensor s = metrics.sensor("test.sensor");
    s.add(metrics.metricName("test.avg", "grp1"), new Avg());
    s.add(metrics.metricName("test.max", "grp1"), new Max());
    s.add(metrics.metricName("test.min", "grp1"), new Min());
    s.add(new Meter(TimeUnit.SECONDS, metrics.metricName("test.rate", "grp1"), metrics.metricName("test.total", "grp1")));
    s.add(new Meter(TimeUnit.SECONDS, new WindowedCount(), metrics.metricName("test.occurences", "grp1"), metrics.metricName("test.occurences.total", "grp1")));
    s.add(metrics.metricName("test.count", "grp1"), new WindowedCount());
    s.add(new Percentiles(100, -100, 100, BucketSizing.CONSTANT, new Percentile(metrics.metricName("test.median", "grp1"), 50.0), new Percentile(metrics.metricName("test.perc99_9", "grp1"), 99.9)));
    Sensor s2 = metrics.sensor("test.sensor2");
    s2.add(metrics.metricName("s2.total", "grp1"), new CumulativeSum());
    s2.record(5.0);
    int sum = 0;
    int count = 10;
    for (int i = 0; i < count; i++) {
        s.record(i);
        sum += i;
    }
    // prior to any time passing
    double elapsedSecs = (config.timeWindowMs() * (config.samples() - 1)) / 1000.0;
    assertEquals(count / elapsedSecs, metricValueFunc.apply(metrics.metrics().get(metrics.metricName("test.occurences", "grp1"))), EPS, String.format("Occurrences(0...%d) = %f", count, count / elapsedSecs));
    // pretend 2 seconds passed...
    long sleepTimeMs = 2;
    time.sleep(sleepTimeMs * 1000);
    elapsedSecs += sleepTimeMs;
    assertEquals(5.0, metricValueFunc.apply(metrics.metric(metrics.metricName("s2.total", "grp1"))), EPS, "s2 reflects the constant value");
    assertEquals(4.5, metricValueFunc.apply(metrics.metric(metrics.metricName("test.avg", "grp1"))), EPS, "Avg(0...9) = 4.5");
    assertEquals(count - 1, metricValueFunc.apply(metrics.metric(metrics.metricName("test.max", "grp1"))), EPS, "Max(0...9) = 9");
    assertEquals(0.0, metricValueFunc.apply(metrics.metric(metrics.metricName("test.min", "grp1"))), EPS, "Min(0...9) = 0");
    assertEquals(sum / elapsedSecs, metricValueFunc.apply(metrics.metric(metrics.metricName("test.rate", "grp1"))), EPS, "Rate(0...9) = 1.40625");
    assertEquals(count / elapsedSecs, metricValueFunc.apply(metrics.metric(metrics.metricName("test.occurences", "grp1"))), EPS, String.format("Occurrences(0...%d) = %f", count, count / elapsedSecs));
    assertEquals(count, metricValueFunc.apply(metrics.metric(metrics.metricName("test.count", "grp1"))), EPS, "Count(0...9) = 10");
}

Example 5 with Percentiles

use of org.apache.kafka.common.metrics.stats.Percentiles in project kafka by apache.

the class MetricsTest method testPercentilesWithRandomNumbersAndLinearBucketing.

@Test
public void testPercentilesWithRandomNumbersAndLinearBucketing() {
    long seed = new Random().nextLong();
    // 100kB
    int sizeInBytes = 100 * 1000;
    // if values are ms, max is 1000 days
    long maximumValue = 1000 * 24 * 60 * 60 * 1000L;
    try {
        Random prng = new Random(seed);
        // range is [5000, 15000]
        int numberOfValues = 5000 + prng.nextInt(10_000);
        Percentiles percs = new Percentiles(sizeInBytes, maximumValue, BucketSizing.LINEAR, new Percentile(metrics.metricName("test.p90", "grp1"), 90), new Percentile(metrics.metricName("test.p99", "grp1"), 99));
        MetricConfig config = new MetricConfig().eventWindow(50).samples(2);
        Sensor sensor = metrics.sensor("test", config);
        sensor.add(percs);
        Metric p90 = this.metrics.metrics().get(metrics.metricName("test.p90", "grp1"));
        Metric p99 = this.metrics.metrics().get(metrics.metricName("test.p99", "grp1"));
        final List<Long> values = new ArrayList<>(numberOfValues);
        // record two windows worth of sequential values
        for (int i = 0; i < numberOfValues; ++i) {
            long value = (Math.abs(prng.nextLong()) - 1) % maximumValue;
            values.add(value);
            sensor.record(value);
        }
        Collections.sort(values);
        int p90Index = (int) Math.ceil(((double) (90 * numberOfValues)) / 100);
        int p99Index = (int) Math.ceil(((double) (99 * numberOfValues)) / 100);
        double expectedP90 = values.get(p90Index - 1);
        double expectedP99 = values.get(p99Index - 1);
        assertEquals(expectedP90, (Double) p90.metricValue(), expectedP90 / 5);
        assertEquals(expectedP99, (Double) p99.metricValue(), expectedP99 / 5);
    } catch (AssertionError e) {
        throw new AssertionError("Assertion failed in randomized test. Reproduce with seed = " + seed + " .", e);
    }
}