Question

我正在编写一个hadoop作业，它处理许多文件并从每个文件创建多个文件。我正在使用“MultipleOutputs”来编写它们。它适用于较少数量的文件但我收到大量文件的以下错误。在MultipleOutputs.write（key，value，outputPath）上引发异常; 我试过增加ulimit和-Xmx，但无济于事。

2013-01-15 13:44:05,154 FATAL org.apache.hadoop.mapred.Child: Error running child : java.lang.OutOfMemoryError: Java heap space
    at org.apache.hadoop.hdfs.DFSOutputStream$Packet.<init>(DFSOutputStream.java:201)
    at org.apache.hadoop.hdfs.DFSOutputStream.writeChunk(DFSOutputStream.java:1423)
    at org.apache.hadoop.fs.FSOutputSummer.writeChecksumChunk(FSOutputSummer.java:161)
    at org.apache.hadoop.fs.FSOutputSummer.flushBuffer(FSOutputSummer.java:136)
    at org.apache.hadoop.fs.FSOutputSummer.flushBuffer(FSOutputSummer.java:125)
    at org.apache.hadoop.fs.FSOutputSummer.write1(FSOutputSummer.java:116)
    at org.apache.hadoop.fs.FSOutputSummer.write(FSOutputSummer.java:90)
    at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.write(FSDataOutputStream.java:54)
    at java.io.DataOutputStream.write(DataOutputStream.java:90)
    at org.apache.hadoop.mapreduce.lib.output.TextOutputFormat$LineRecordWriter. writeObject( TextOutputFormat.java:78)
    at org.apache.hadoop.mapreduce.lib.output.TextOutputFormat$LineRecordWriter. write(TextOutputFormat.java:99)
    **at org.apache.hadoop.mapreduce.lib.output.MultipleOutputs.write( MultipleOutputs.java:386)
    at com.demoapp.collector.MPReducer.reduce(MPReducer.java:298)
    at com.demoapp.collector.MPReducer.reduce(MPReducer.java:28)**
    at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:164)
    at org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:595)
    at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:433)
    at org.apache.hadoop.mapred.Child$4.run(Child.java:268)
    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:1332)
    at org.apache.hadoop.mapred.Child.main(Child.java:262)

有什么想法吗？

Answer 1

如果它不适用于大量文件，可能是因为您已经达到了datanode可以提供的最大文件数。这可以通过hdfs-site.xml中名为dfs.datanode.max.xcievers的属性来控制。

根据建议的here，您应该将其价值提升到允许您的作业正常运行的值，他们建议4096：

<property>
    <name>dfs.datanode.max.xcievers</name>
    <value>4096</value>
</property>

Answer 2

我将reduce任务的数量从1增加到8，并将io.sort.mb的值增加到mapred.task.timeout。

Details

此链接有用 - Cloudera blog

Hadoop - MultipleOutputs.write - OutofMemory - Java堆空间

2 个答案: