kafka Percentiles 源码

  • 2022-10-20
  • 浏览 (503)

kafka Percentiles 代码

文件路径:/clients/src/main/java/org/apache/kafka/common/metrics/stats/Percentiles.java

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements. See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License. You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.kafka.common.metrics.stats;

import java.util.ArrayList;
import java.util.List;

import org.apache.kafka.common.metrics.CompoundStat;
import org.apache.kafka.common.metrics.MetricConfig;
import org.apache.kafka.common.metrics.stats.Histogram.BinScheme;
import org.apache.kafka.common.metrics.stats.Histogram.ConstantBinScheme;
import org.apache.kafka.common.metrics.stats.Histogram.LinearBinScheme;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * A compound stat that reports one or more percentiles
 */
public class Percentiles extends SampledStat implements CompoundStat {

    private final Logger log = LoggerFactory.getLogger(Percentiles.class);

    public enum BucketSizing {
        CONSTANT, LINEAR
    }

    private final int buckets;
    private final Percentile[] percentiles;
    private final BinScheme binScheme;
    private final double min;
    private final double max;

    public Percentiles(int sizeInBytes, double max, BucketSizing bucketing, Percentile... percentiles) {
        this(sizeInBytes, 0.0, max, bucketing, percentiles);
    }

    public Percentiles(int sizeInBytes, double min, double max, BucketSizing bucketing, Percentile... percentiles) {
        super(0.0);
        this.percentiles = percentiles;
        this.buckets = sizeInBytes / 4;
        this.min = min;
        this.max = max;
        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 {
            throw new IllegalArgumentException("Unknown bucket type: " + bucketing);
        }
    }

    @Override
    public List<NamedMeasurable> stats() {
        List<NamedMeasurable> ms = new ArrayList<>(this.percentiles.length);
        for (Percentile percentile : this.percentiles) {
            final double pct = percentile.percentile();
            ms.add(new NamedMeasurable(
                percentile.name(),
                (config, now) -> value(config, now, pct / 100.0))
            );
        }
        return ms;
    }

    public double value(MetricConfig config, long now, double quantile) {
        purgeObsoleteSamples(config, now);
        float count = 0.0f;
        for (Sample sample : this.samples)
            count += sample.eventCount;
        if (count == 0.0f)
            return Double.NaN;
        float sum = 0.0f;
        float quant = (float) quantile;
        for (int b = 0; b < buckets; b++) {
            for (Sample s : this.samples) {
                HistogramSample sample = (HistogramSample) s;
                float[] hist = sample.histogram.counts();
                sum += hist[b];
                if (sum / count > quant)
                    return binScheme.fromBin(b);
            }
        }
        return Double.POSITIVE_INFINITY;
    }

    @Override
    public double combine(List<Sample> samples, MetricConfig config, long now) {
        return value(config, now, 0.5);
    }

    @Override
    protected HistogramSample newSample(long timeMs) {
        return new HistogramSample(this.binScheme, timeMs);
    }

    @Override
    protected void update(Sample sample, MetricConfig config, double value, long timeMs) {
        final double boundedValue;
        if (value > max) {
            log.debug("Received value {} which is greater than max recordable value {}, will be pinned to the max value",
                     value, max);
            boundedValue = max;
        } else if (value < min) {
            log.debug("Received value {} which is less than min recordable value {}, will be pinned to the min value",
                     value, min);
            boundedValue = min;
        } else {
            boundedValue = value;
        }

        HistogramSample hist = (HistogramSample) sample;
        hist.histogram.record(boundedValue);
    }

    private static class HistogramSample extends SampledStat.Sample {
        private final Histogram histogram;

        private HistogramSample(BinScheme scheme, long now) {
            super(0.0, now);
            this.histogram = new Histogram(scheme);
        }

        @Override
        public void reset(long now) {
            super.reset(now);
            this.histogram.clear();
        }
    }

}

相关信息

kafka 源码目录

相关文章

kafka Avg 源码

kafka CumulativeCount 源码

kafka CumulativeSum 源码

kafka Frequencies 源码

kafka Frequency 源码

kafka Histogram 源码

kafka Max 源码

kafka Meter 源码

kafka Min 源码

kafka Percentile 源码

0  赞