Package org.apache.kafka.common.metrics.stats.Histogram

Examples of org.apache.kafka.common.metrics.stats.Histogram.ConstantBinScheme

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    public Percentiles(int sizeInBytes, double min, double max, BucketSizing bucketing, Percentile... percentiles) {
        super(0.0);
        this.percentiles = percentiles;
        this.buckets = sizeInBytes / 4;
        if (bucketing == BucketSizing.CONSTANT) {
            this.binScheme = new ConstantBinScheme(buckets, min, max);
        } else if (bucketing == BucketSizing.LINEAR) {
            if (min != 0.0d)
                throw new IllegalArgumentException("Linear bucket sizing requires min to be 0.0.");
            this.binScheme = new LinearBinScheme(buckets, max);
        } else {
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    private static final double EPS = 0.0000001d;

    @Test
    public void testHistogram() {
        BinScheme scheme = new ConstantBinScheme(12, -5, 5);
        Histogram hist = new Histogram(scheme);
        for (int i = -5; i < 5; i++)
            hist.record(i);
        for (int i = 0; i < 10; i++)
            assertEquals(scheme.fromBin(i + 1), hist.value(i / 10.0 + EPS), EPS);
    }
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            assertEquals(scheme.fromBin(i + 1), hist.value(i / 10.0 + EPS), EPS);
    }

    @Test
    public void testConstantBinScheme() {
        ConstantBinScheme scheme = new ConstantBinScheme(5, -5, 5);
        assertEquals("A value below the lower bound should map to the first bin", 0, scheme.toBin(-5.01));
        assertEquals("A value above the upper bound should map to the last bin", 4, scheme.toBin(5.01));
        assertEquals("Check boundary of bucket 1", 1, scheme.toBin(-5));
        assertEquals("Check boundary of bucket 4", 4, scheme.toBin(5));
        assertEquals("Check boundary of bucket 3", 3, scheme.toBin(4.9999));
        checkBinningConsistency(new ConstantBinScheme(4, 0, 5));
        checkBinningConsistency(scheme);
    }
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    }

    public static void main(String[] args) {
        Random random = new Random();
        System.out.println("[-100, 100]:");
        for (BinScheme scheme : Arrays.asList(new ConstantBinScheme(1000, -100, 100),
                                              new ConstantBinScheme(100, -100, 100),
                                              new ConstantBinScheme(10, -100, 100))) {
            Histogram h = new Histogram(scheme);
            for (int i = 0; i < 10000; i++)
                h.record(200.0 * random.nextDouble() - 100.0);
            for (double quantile = 0.0; quantile < 1.0; quantile += 0.05)
                System.out.printf("%5.2f: %.1f, ", quantile, h.value(quantile));
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Related Classes of org.apache.kafka.common.metrics.stats.Histogram.ConstantBinScheme

  • org.apache.kafka.common.metrics.stats.HistogramTest
  • org.apache.kafka.common.metrics.stats.Percentiles
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