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ShuffleError 错误信息：

Error: org.apache.hadoop.mapreduce.task.reduce.Shuffle$ShuffleError: error in shuffle in fetcher#3
at org.apache.hadoop.mapreduce.task.reduce.Shuffle.run(Shuffle.java:134)
at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:376)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:164)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1693)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158) 
Caused by: java.lang.OutOfMemoryError: Java heap space
at org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:56)
at org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:46)
at org.apache.hadoop.mapreduce.task.reduce.InMemoryMapOutput.<init>(InMemoryMapOutput.java:63)
at org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl.unconditionalReserve(MergeManagerImpl.java:305)
at org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl.reserve(MergeManagerImpl.java:295)
at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyMapOutput(Fetcher.java:514)
at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:336)
at org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:193)

Cause 原因：reduce会在map执行到一定比例启动多个fetch线程去拉取map的输出结果，放到reduce的内存、磁盘中，然后进行merge。当数据量大时，拉取到内存的数据就会引起OOM，所以此时要减少fetch占内存的百分比，将fetch的数据直接放在磁盘上。

有关参数：

mapreduce.reduce.shuffle.memory.limit.percent

Default Configuration 默认参数：

<property>
   <name>mapreduce.reduce.shuffle.memory.limit.percent</name>
  <value>0.25</value>
  <description>Expert: Maximum percentage of the in-memory limit that a
  single shuffle can consume</description>
</property>

OR 或者

hive>set mapreduce.reduce.shuffle.memory.limit.percent;
mapreduce.reduce.shuffle.memory.limit.percent=0.25

Solution 处理方案：限制reduce的shuffle内存使用

hive sql

如果是hive sql,在sql执行之前，增加如下语句：

set mapreduce.reduce.shuffle.memory.limit.percent=0.15;

MapReduce

如果是 MapReduce 程序，在job conf中设置如下:

job.getConfiguration().setStrings("mapreduce.reduce.shuffle.memory.limit.percent", "0.15");

其他参考：

http://www.sqlparty.com/yarn在shuffle阶段内存不足问题error-in-shuffle-in-fetcher/

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