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/**
 * 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.hadoop.metrics2.lib;

import java.io.Closeable;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import java.util.Map.Entry;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.Executors;
import java.util.concurrent.LinkedBlockingDeque;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.ScheduledFuture;
import java.util.concurrent.TimeUnit;
import java.util.function.Function;

import com.google.common.annotations.VisibleForTesting;
import org.apache.commons.lang3.StringUtils;
import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.hadoop.metrics2.MetricsInfo;
import org.apache.hadoop.metrics2.MetricsRecordBuilder;
import org.apache.hadoop.metrics2.impl.MetricsCollectorImpl;

import com.google.common.base.Preconditions;
import com.google.common.util.concurrent.ThreadFactoryBuilder;

import javax.annotation.Nullable;

import static org.apache.hadoop.metrics2.lib.Interns.*;

/**
 * 

* This class maintains a group of rolling average metrics. It implements the * algorithm of rolling average, i.e. a number of sliding windows are kept to * roll over and evict old subsets of samples. Each window has a subset of * samples in a stream, where sub-sum and sub-total are collected. All sub-sums * and sub-totals in all windows will be aggregated to final-sum and final-total * used to compute final average, which is called rolling average. *

*/ @InterfaceAudience.Public @InterfaceStability.Evolving public class MutableRollingAverages extends MutableMetric implements Closeable { private MutableRatesWithAggregation innerMetrics = new MutableRatesWithAggregation(); @VisibleForTesting static final ScheduledExecutorService SCHEDULER = Executors .newScheduledThreadPool(1, new ThreadFactoryBuilder().setDaemon(true) .setNameFormat("MutableRollingAverages-%d").build()); private ScheduledFuture scheduledTask = null; @Nullable private Map currentSnapshot; private final String avgInfoNameTemplate; private final String avgInfoDescTemplate; private int numWindows; private static class SumAndCount { private final double sum; private final long count; SumAndCount(final double sum, final long count) { this.sum = sum; this.count = count; } public double getSum() { return sum; } public long getCount() { return count; } } /** *

* key: metric name *

*

* value: deque where sub-sums and sub-totals for sliding windows are * maintained. *

*/ private Map> averages = new ConcurrentHashMap<>(); private static final long WINDOW_SIZE_MS_DEFAULT = 300_000; private static final int NUM_WINDOWS_DEFAULT = 36; /** * Constructor for {@link MutableRollingAverages}. * @param metricValueName */ public MutableRollingAverages(String metricValueName) { if (metricValueName == null) { metricValueName = ""; } avgInfoNameTemplate = "[%s]" + "RollingAvg" + StringUtils.capitalize(metricValueName); avgInfoDescTemplate = "Rolling average " + StringUtils.uncapitalize(metricValueName) +" for "+ "%s"; numWindows = NUM_WINDOWS_DEFAULT; scheduledTask = SCHEDULER.scheduleAtFixedRate(new RatesRoller(this), WINDOW_SIZE_MS_DEFAULT, WINDOW_SIZE_MS_DEFAULT, TimeUnit.MILLISECONDS); } /** * This method is for testing only to replace the scheduledTask. */ @VisibleForTesting synchronized void replaceScheduledTask(int windows, long interval, TimeUnit timeUnit) { numWindows = windows; scheduledTask.cancel(true); scheduledTask = SCHEDULER.scheduleAtFixedRate(new RatesRoller(this), interval, interval, timeUnit); } @Override public void snapshot(MetricsRecordBuilder builder, boolean all) { if (all || changed()) { for (final Entry> entry : averages.entrySet()) { final String name = entry.getKey(); final MetricsInfo avgInfo = info( String.format(avgInfoNameTemplate, StringUtils.capitalize(name)), String.format(avgInfoDescTemplate, StringUtils.uncapitalize(name))); double totalSum = 0; long totalCount = 0; for (final SumAndCount sumAndCount : entry.getValue()) { totalCount += sumAndCount.getCount(); totalSum += sumAndCount.getSum(); } if (totalCount != 0) { builder.addGauge(avgInfo, totalSum / totalCount); } } if (changed()) { clearChanged(); } } } /** * Collects states maintained in {@link ThreadLocal}, if any. */ public void collectThreadLocalStates() { innerMetrics.collectThreadLocalStates(); } /** * @param name * name of metric * @param value * value of metric */ public void add(final String name, final long value) { innerMetrics.add(name, value); } private static class RatesRoller implements Runnable { private final MutableRollingAverages parent; RatesRoller(final MutableRollingAverages parent) { this.parent = parent; } @Override public void run() { synchronized (parent) { final MetricsCollectorImpl mc = new MetricsCollectorImpl(); final MetricsRecordBuilder rb = mc.addRecord("RatesRoller"); /** * snapshot all metrics regardless of being changed or not, in case no * ops since last snapshot, we will get 0. */ parent.innerMetrics.snapshot(rb, true); Preconditions.checkState(mc.getRecords().size() == 1, "There must be only one record and it's named with 'RatesRoller'"); parent.currentSnapshot = parent.innerMetrics.getGlobalMetrics(); parent.rollOverAvgs(); } parent.setChanged(); } } /** * Iterates over snapshot to capture all Avg metrics into rolling structure * {@link MutableRollingAverages#averages}. */ private synchronized void rollOverAvgs() { if (currentSnapshot == null) { return; } for (Map.Entry entry : currentSnapshot.entrySet()) { final MutableRate rate = entry.getValue(); final LinkedBlockingDeque deque = averages.computeIfAbsent( entry.getKey(), new Function>() { @Override public LinkedBlockingDeque apply(String k) { return new LinkedBlockingDeque<>(numWindows); } }); final SumAndCount sumAndCount = new SumAndCount( rate.lastStat().total(), rate.lastStat().numSamples()); /* put newest sum and count to the end */ if (!deque.offerLast(sumAndCount)) { deque.pollFirst(); deque.offerLast(sumAndCount); } } setChanged(); } @Override public void close() throws IOException { if (scheduledTask != null) { scheduledTask.cancel(false); } scheduledTask = null; } /** * Retrieve a map of metric name {@literal ->} (aggregate). * Filter out entries that don't have at least minSamples. * * @return a map of peer DataNode Id to the average latency to that * node seen over the measurement period. */ public synchronized Map getStats(long minSamples) { final Map stats = new HashMap<>(); for (final Entry> entry : averages.entrySet()) { final String name = entry.getKey(); double totalSum = 0; long totalCount = 0; for (final SumAndCount sumAndCount : entry.getValue()) { totalCount += sumAndCount.getCount(); totalSum += sumAndCount.getSum(); } if (totalCount > minSamples) { stats.put(name, totalSum / totalCount); } } return stats; } }




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