java - Hadoop：作业在较小的数据集上运行良好，但在大型数据集上失败

Question

我有以下情况

我有 3 台机器集群，配置如下。

Master

Usage of /:   91.4% of 74.41GB 
MemTotal:       16557308 kB
MemFree:          723736 kB

Slave 01

Usage of /:   52.9% of 29.76GB
MemTotal:       16466220 kB 
MemFree:         5320860 kB

Slave 02

Usage of /:   19.0% of 19.84GB
MemTotal:       16466220 kB
MemFree:         6173564 kB

hadoop/conf/core-site.xml

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!-- Put site-specific property overrides in this file. -->

<configuration>
<property>
  <name>hadoop.tmp.dir</name>
  <value>/work/app/hadoop/tmp</value>
  <description>A base for other temporary directories.</description>
</property>

<property>
  <name>fs.default.name</name>
  <value>hdfs://master:54310</value>
  <description>The name of the default file system.  A URI whose
  scheme and authority determine the FileSystem implementation.  The
  uri's scheme determines the config property (fs.SCHEME.impl) naming
  the FileSystem implementation class.  The uri's authority is used to
  determine the host, port, etc. for a filesystem.</description>
</property>
<property>
  <name>dfs.datanode.max.xcievers</name>
  <value>4096</value>
</property>
</configuration>

hadoop/conf/mapred-site.xml

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!-- Put site-specific property overrides in this file. -->

<configuration>
<property>
  <name>mapred.job.tracker</name>
  <value>master:54311</value>
  <description>The host and port that the MapReduce job tracker runs
  at.  If "local", then jobs are run in-process as a single map
  and reduce task.
  </description>
</property>

<property>
  <name>mapred.reduce.tasks</name>
  <value>1</value>
</property>

<property>
  <name>mapred.map.tasks</name>
  <value>100</value>
</property>

<property>
  <name>mapred.task.timeout</name>
  <value>0</value>
</property>

<property>
  <name>mapred.child.java.opts</name>
  <value>-Xmx512m</value>
</property>
</configuration>

hadoop/conf/hdfs-site.xml

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!-- Put site-specific property overrides in this file. -->

<configuration>
<property>
  <name>dfs.replication</name>
  <value>3</value>
  <description>Default block replication.
  The actual number of replications can be specified when the file is created.
  The default is used if replication is not specified in create time.
  </description>
</property>
<property>
  <name>dfs.datanode.socket.write.timeout</name>
  <value>0</value>
</property>
</configuration>

我有超过 200 万个 XML 文档（每个文档大小 ~ 400 KB）
map任务打开这些xml中的每一个并将它们作为JSON
reduce任务将这些中的每一个都JSON作为字符串，应用转换并发出它
不。任务- map100
不。任务- reduce01
整个工作运行良好时number of documents = 10,000
什么时候number of documents = 278262，作业失败，我看到以下各种问题

在网页界面上

在 slave-01、slave-02 上

java.lang.Throwable: Child Error
    at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:271)
Caused by: java.io.IOException: Task process exit with nonzero status of 255.
    at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:258)

在主人

java.lang.RuntimeException: java.io.IOException: Spill failed
    at org.apache.hadoop.streaming.PipeMapRed.waitOutputThreads(PipeMapRed.java:325)
    at org.apache.hadoop.streaming.PipeMapRed.mapRedFinished(PipeMapRed.java:545)
    at org.apache.hadoop.streaming.PipeMapper.close(PipeMapper.java:132)
    at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:57)
    at org.apache.hadoop.streaming.PipeMapRunner.run(PipeMapRunner.java:36)
    at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:436)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:372)
    at org.apache.hadoop.mapred.Child$4.run(Child.java:261)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:396)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1059)
    at org.apache.hadoop.mapred.Child.main(Child.java:255)
Caused by: java.io.IOException: Spill failed
    at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.collect(MapTask.java:1029)
    at org.apache.hadoop.mapred.MapTask$OldOutputCollector.collect(MapTask.java:592)
    at org.apache.hadoop.streaming.PipeMapRed$MROutputThread.run(PipeMapRed.java:381)
Caused by: org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find any valid local directory for output/spill1.out
    at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:381)
    at org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
    at org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:127)
    at org.apache.hadoop.mapred.MapOutputFile.getSpillFileForWrite(MapOutputFile.java:121)
    at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.sortAndSpill(MapTask.java:1392)
    at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.access$1800(MapTask.java:853)
    at org.apache.hadoop.mapred.MapTask$MapOutputBuffer$SpillThread.run(MapTask.java:1344)

java.lang.Throwable: Child Error
    at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:271)
Caused by: java.io.IOException: Creation of /work/app/hadoop/tmp/mapred/local/userlogs/job_201207220051_0001/attempt_201207220051_0001_m_000004_2 failed.
    at org.apache.hadoop.mapred.TaskLog.createTaskAttemptLogDir(TaskLog.java:102)
    at org.apache.hadoop.mapred.DefaultTaskController.createLogDir(DefaultTaskController.java:71)
    at org.apache.hadoop.mapred.TaskRunner.prepareLogFiles(TaskRunner.java:316)
    at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:228)

-------
java.lang.Throwable: Child Error
    at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:271)
Caused by: java.io.IOException: Creation of /work/app/hadoop/tmp/mapred/local/userlogs/job_201207220051_0001/attempt_201207220051_0001_m_000004_2.cleanup failed.
    at org.apache.hadoop.mapred.TaskLog.createTaskAttemptLogDir(TaskLog.java:102)
    at org.apache.hadoop.mapred.DefaultTaskController.createLogDir(DefaultTaskController.java:71)
    at org.apache.hadoop.mapred.TaskRunner.prepareLogFiles(TaskRunner.java:316)
    at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:228)

当我去检查登录时slaves，这就是我发现的hadoop-hduser-datanode-hadoop-01.log

2012-07-22 09:26:52,795 INFO org.apache.hadoop.hdfs.server.datanode.DataNode: Receiving block blk_-5384386931827098009_1010 src: /10.0.0.81:51402 dest: /10.0.0.82:50010
2012-07-22 09:26:52,800 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: IOException in BlockReceiver constructor. Cause is 
2012-07-22 09:26:52,800 INFO org.apache.hadoop.hdfs.server.datanode.DataNode: writeBlock blk_-5384386931827098009_1010 received exception java.io.IOException: Unexpected problem in creating temporary file for blk_-5384386931827098009_1010.  File /work/app/hadoop/tmp/dfs/data/tmp/blk_-5384386931827098009 should not be present, but is.
2012-07-22 09:26:52,800 ERROR org.apache.hadoop.hdfs.server.datanode.DataNode: DatanodeRegistration(10.0.0.82:50010, storageID=DS-735951984-127.0.1.1-50010-1342943517618, infoPort=50075, ipcPort=50020):DataXceiver
java.io.IOException: Unexpected problem in creating temporary file for blk_-5384386931827098009_1010.  File /work/app/hadoop/tmp/dfs/data/tmp/blk_-5384386931827098009 should not be present, but is.
        at org.apache.hadoop.hdfs.server.datanode.FSDataset$FSVolume.createTmpFile(FSDataset.java:426)
        at org.apache.hadoop.hdfs.server.datanode.FSDataset$FSVolume.createTmpFile(FSDataset.java:404)
        at org.apache.hadoop.hdfs.server.datanode.FSDataset.createTmpFile(FSDataset.java:1249)
        at org.apache.hadoop.hdfs.server.datanode.FSDataset.writeToBlock(FSDataset.java:1138)
        at org.apache.hadoop.hdfs.server.datanode.BlockReceiver.<init>(BlockReceiver.java:99)
        at org.apache.hadoop.hdfs.server.datanode.DataXceiver.writeBlock(DataXceiver.java:299)
        at org.apache.hadoop.hdfs.server.datanode.DataXceiver.run(DataXceiver.java:107)
        at java.lang.Thread.run(Thread.java:662)

请帮助我了解我需要做什么才能解决此问题？

score 14 · Accepted Answer

由于您有多个 reducer，因此您的映射器会将输出写入从属设备上的本地磁盘（而不是在 HDFS 中）。更准确地说，映射器实际上不会立即写入本地磁盘。相反，它们会在内存中缓冲输出，直到达到阈值（请参阅“io.sort.mb”配置设置）。这个过程称为溢出。我认为问题在于，当 Hadoop 试图溢出到磁盘时，您的从属服务器没有足够的磁盘空间来保存映射器生成的所有数据。

您提到每个映射器都会生成一个 json 字符串。假设每个文档约为 100KB（可能甚至比这更大），它将达到 278,262 x 100KB = ~28GB，并且您的两个从属服务器每个都有大约 15GB 的可用空间。

我认为最简单的方法是使用以下两个配置设置压缩映射器的即时输出：

<property>
  <name> mapreduce.map.output.compress</name> 
  <value>true</value>
</property>
<property>
  <name>mapreduce.map.output.compress.codec</name>
  <value>org.apache.hadoop.io.compress.GzipCodec</value>
</property>

由于您的数据都是 JSON/文本数据，我认为您将受益于 Hadoop 支持的任何压缩算法。

仅供参考，如果您的文档大小超过 200 万，您应该考虑为您的主文件添加更多内存。根据经验，每个文件/目录/块占用大约 150 个字节（或每 100 万个文件 300MB）。然而，实际上，我会为每 100 万个文件保留 1GB。

score 0 · Accepted Answer

我遇到了同样的问题（在 Mac OS X 上）并通过在 mapred-site.xml 中设置以下值来解决它

<name>mapred.child.ulimit</name>
<value>unlimited</value>

然后我停止了 hadoop 服务bin/stop-all.sh，删除了 /usr/local/tmp/ 文件夹，格式化了 namenodebin/hadoop namenode -format并启动了 hadoop 服务bin/start-all.sh

java - Hadoop：作业在较小的数据集上运行良好，但在大型数据集上失败

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