MAPREDUCE-6024. Shortened the time when Fetcher is stuck in retrying before concluding the failure by configuration. Contributed by Yunjiong Zhao.

svn merge --ignore-ancestry -c 1618677 ../../trunk/


git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/branches/branch-2@1618679 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Zhijie Shen 2014-08-18 17:59:32 +00:00
parent 03a33d0f91
commit 570183a437
5 changed files with 57 additions and 18 deletions

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@ -81,6 +81,9 @@ Release 2.6.0 - UNRELEASED
MAPREDUCE-6032. Made MR jobs write job history files on the default FS when
the current context's FS is different. (Benjamin Zhitomirsky via zjshen)
MAPREDUCE-6024. Shortened the time when Fetcher is stuck in retrying before
concluding the failure by configuration. (Yunjiong Zhao via zjshen)
Release 2.5.0 - UNRELEASED
INCOMPATIBLE CHANGES

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@ -148,10 +148,10 @@ public class JobImpl implements org.apache.hadoop.mapreduce.v2.app.job.Job,
private static final Log LOG = LogFactory.getLog(JobImpl.class);
//The maximum fraction of fetch failures allowed for a map
private static final double MAX_ALLOWED_FETCH_FAILURES_FRACTION = 0.5;
// Maximum no. of fetch-failure notifications after which map task is failed
private static final int MAX_FETCH_FAILURES_NOTIFICATIONS = 3;
private float maxAllowedFetchFailuresFraction;
//Maximum no. of fetch-failure notifications after which map task is failed
private int maxFetchFailuresNotifications;
public static final String JOB_KILLED_DIAG =
"Job received Kill while in RUNNING state.";
@ -704,6 +704,13 @@ public class JobImpl implements org.apache.hadoop.mapreduce.v2.app.job.Job,
if(forcedDiagnostic != null) {
this.diagnostics.add(forcedDiagnostic);
}
this.maxAllowedFetchFailuresFraction = conf.getFloat(
MRJobConfig.MAX_ALLOWED_FETCH_FAILURES_FRACTION,
MRJobConfig.DEFAULT_MAX_ALLOWED_FETCH_FAILURES_FRACTION);
this.maxFetchFailuresNotifications = conf.getInt(
MRJobConfig.MAX_FETCH_FAILURES_NOTIFICATIONS,
MRJobConfig.DEFAULT_MAX_FETCH_FAILURES_NOTIFICATIONS);
}
protected StateMachine<JobStateInternal, JobEventType, JobEvent> getStateMachine() {
@ -1900,9 +1907,8 @@ public class JobImpl implements org.apache.hadoop.mapreduce.v2.app.job.Job,
float failureRate = shufflingReduceTasks == 0 ? 1.0f :
(float) fetchFailures / shufflingReduceTasks;
// declare faulty if fetch-failures >= max-allowed-failures
boolean isMapFaulty =
(failureRate >= MAX_ALLOWED_FETCH_FAILURES_FRACTION);
if (fetchFailures >= MAX_FETCH_FAILURES_NOTIFICATIONS && isMapFaulty) {
if (fetchFailures >= job.getMaxFetchFailuresNotifications()
&& failureRate >= job.getMaxAllowedFetchFailuresFraction()) {
LOG.info("Too many fetch-failures for output of task attempt: " +
mapId + " ... raising fetch failure to map");
job.eventHandler.handle(new TaskAttemptEvent(mapId,
@ -2185,4 +2191,12 @@ public class JobImpl implements org.apache.hadoop.mapreduce.v2.app.job.Job,
jobConf.addResource(fc.open(confPath), confPath.toString());
return jobConf;
}
public float getMaxAllowedFetchFailuresFraction() {
return maxAllowedFetchFailuresFraction;
}
public int getMaxFetchFailuresNotifications() {
return maxFetchFailuresNotifications;
}
}

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@ -288,11 +288,19 @@ public interface MRJobConfig {
public static final String SHUFFLE_READ_TIMEOUT = "mapreduce.reduce.shuffle.read.timeout";
public static final String SHUFFLE_FETCH_FAILURES = "mapreduce.reduce.shuffle.maxfetchfailures";
public static final String MAX_ALLOWED_FETCH_FAILURES_FRACTION = "mapreduce.reduce.shuffle.max-fetch-failures-fraction";
public static final float DEFAULT_MAX_ALLOWED_FETCH_FAILURES_FRACTION = 0.5f;
public static final String MAX_FETCH_FAILURES_NOTIFICATIONS = "mapreduce.reduce.shuffle.max-fetch-failures-notifications";
public static final int DEFAULT_MAX_FETCH_FAILURES_NOTIFICATIONS = 3;
public static final String SHUFFLE_NOTIFY_READERROR = "mapreduce.reduce.shuffle.notify.readerror";
public static final String MAX_SHUFFLE_FETCH_RETRY_DELAY = "mapreduce.reduce.shuffle.retry-delay.max.ms";
public static final long DEFAULT_MAX_SHUFFLE_FETCH_RETRY_DELAY = 60000;
public static final String MAX_SHUFFLE_FETCH_HOST_FAILURES = "mapreduce.reduce.shuffle.max-host-failures";
public static final int DEFAULT_MAX_SHUFFLE_FETCH_HOST_FAILURES = 5;
public static final String REDUCE_SKIP_INCR_PROC_COUNT = "mapreduce.reduce.skip.proc-count.auto-incr";

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@ -319,6 +319,7 @@ class Fetcher<K,V> extends Thread {
// If connect did not succeed, just mark all the maps as failed,
// indirectly penalizing the host
scheduler.hostFailed(host.getHostName());
for(TaskAttemptID left: remaining) {
scheduler.copyFailed(left, host, false, connectExcpt);
}
@ -343,6 +344,7 @@ class Fetcher<K,V> extends Thread {
if(failedTasks != null && failedTasks.length > 0) {
LOG.warn("copyMapOutput failed for tasks "+Arrays.toString(failedTasks));
scheduler.hostFailed(host.getHostName());
for(TaskAttemptID left: failedTasks) {
scheduler.copyFailed(left, host, true, false);
}

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@ -18,7 +18,6 @@
package org.apache.hadoop.mapreduce.task.reduce;
import java.io.IOException;
import java.net.InetAddress;
import java.net.URI;
import java.net.UnknownHostException;
@ -101,6 +100,7 @@ public class ShuffleSchedulerImpl<K,V> implements ShuffleScheduler<K,V> {
private final boolean reportReadErrorImmediately;
private long maxDelay = MRJobConfig.DEFAULT_MAX_SHUFFLE_FETCH_RETRY_DELAY;
private int maxHostFailures;
public ShuffleSchedulerImpl(JobConf job, TaskStatus status,
TaskAttemptID reduceId,
@ -132,6 +132,9 @@ public class ShuffleSchedulerImpl<K,V> implements ShuffleScheduler<K,V> {
this.maxDelay = job.getLong(MRJobConfig.MAX_SHUFFLE_FETCH_RETRY_DELAY,
MRJobConfig.DEFAULT_MAX_SHUFFLE_FETCH_RETRY_DELAY);
this.maxHostFailures = job.getInt(
MRJobConfig.MAX_SHUFFLE_FETCH_HOST_FAILURES,
MRJobConfig.DEFAULT_MAX_SHUFFLE_FETCH_HOST_FAILURES);
}
@Override
@ -213,9 +216,18 @@ public class ShuffleSchedulerImpl<K,V> implements ShuffleScheduler<K,V> {
progress.setStatus("copy(" + mapsDone + " of " + totalMaps + " at "
+ mbpsFormat.format(transferRate) + " MB/s)");
}
public synchronized void hostFailed(String hostname) {
if (hostFailures.containsKey(hostname)) {
IntWritable x = hostFailures.get(hostname);
x.set(x.get() + 1);
} else {
hostFailures.put(hostname, new IntWritable(1));
}
}
public synchronized void copyFailed(TaskAttemptID mapId, MapHost host,
boolean readError, boolean connectExcpt) {
boolean readError, boolean connectExcpt) {
host.penalize();
int failures = 1;
if (failureCounts.containsKey(mapId)) {
@ -226,12 +238,9 @@ public class ShuffleSchedulerImpl<K,V> implements ShuffleScheduler<K,V> {
failureCounts.put(mapId, new IntWritable(1));
}
String hostname = host.getHostName();
if (hostFailures.containsKey(hostname)) {
IntWritable x = hostFailures.get(hostname);
x.set(x.get() + 1);
} else {
hostFailures.put(hostname, new IntWritable(1));
}
//report failure if already retried maxHostFailures times
boolean hostFail = hostFailures.get(hostname).get() > getMaxHostFailures() ? true : false;
if (failures >= abortFailureLimit) {
try {
throw new IOException(failures + " failures downloading " + mapId);
@ -240,7 +249,7 @@ public class ShuffleSchedulerImpl<K,V> implements ShuffleScheduler<K,V> {
}
}
checkAndInformJobTracker(failures, mapId, readError, connectExcpt);
checkAndInformJobTracker(failures, mapId, readError, connectExcpt, hostFail);
checkReducerHealth();
@ -270,9 +279,9 @@ public class ShuffleSchedulerImpl<K,V> implements ShuffleScheduler<K,V> {
// after every 'maxFetchFailuresBeforeReporting' failures
private void checkAndInformJobTracker(
int failures, TaskAttemptID mapId, boolean readError,
boolean connectExcpt) {
boolean connectExcpt, boolean hostFailed) {
if (connectExcpt || (reportReadErrorImmediately && readError)
|| ((failures % maxFetchFailuresBeforeReporting) == 0)) {
|| ((failures % maxFetchFailuresBeforeReporting) == 0) || hostFailed) {
LOG.info("Reporting fetch failure for " + mapId + " to jobtracker.");
status.addFetchFailedMap((org.apache.hadoop.mapred.TaskAttemptID) mapId);
}
@ -507,4 +516,7 @@ public class ShuffleSchedulerImpl<K,V> implements ShuffleScheduler<K,V> {
referee.join();
}
public int getMaxHostFailures() {
return maxHostFailures;
}
}