今天在集群上看到有两个任务跑失败了：
Err log:
In order to change the average load for a reducer (in bytes):
set hive.exec.reducers.bytes.per.reducer=
In order to limit the maximum number of reducers:
set hive.exec.reducers.max=
In order to set a constant number of reducers:
set mapreduce.job.reduces=
java.io.IOException: Bad connect ack with firstBadLink as 192.168.44.57:50010
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.createBlockOutputStream(DFSOutputStream.java:1460)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1361)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:588)
Job Submission failed with exception 'java.io.IOException(Bad connect ack with firstBadLink as 192.168.44.57:50010)'
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask
MapReduce Jobs Launched:
Stage-Stage-1: Map: 16 Reduce: 8 Cumulative CPU: 677.62 sec HDFS Read: 1794135673 HDFS Write: 136964041 SUCCESS
Stage-Stage-5: Map: 16 Reduce: 8 Cumulative CPU: 864.95 sec HDFS Read: 1794135673 HDFS Write: 120770083 SUCCESS
Stage-Stage-4: Map: 70 Reduce: 88 Cumulative CPU: 5431.46 sec HDFS Read: 22519878178 HDFS Write: 422001541 SUCCESS
Total MapReduce CPU Time Spent: 0 days 1 hours 56 minutes 14 seconds 30 msec
task BFD_JOB_TASK_521_20150721041704 is complete.
错误的大概意思是：Job在在运行Map的时候，map的输出正准备往磁盘上写的时候，报：
java.io.IOException: Bad connect ack with firstBadLink as 192.168.44.57:5001了
原因是：
Datanode往hdfs上写时，实际上是通过使用xcievers这个中间服务往linux上的文件系统上写文件的。其实这个xcievers就是一些负责在DataNode和本地磁盘上读，写文件的线程。
DataNode上Block越多，这个线程的数量就应该越多。然后问题来了，这个线程数有个上线（默认是配置的4096）。所以，当Datenode上的Block数量过多时，就会有些Block文件找不到
线程来负责他的读和写工作了。所以就出现了上面的错误（写块失败）。
解决方案是：
在hdfs-site.xml中添加：
Tips:
这个漏洞还可能照成这个错误：
10/12/08 20:10:31 INFO hdfs.DFSClient: Could not obtain block
blk_XXXXXXXXXXXXXXXXXXXXXX_YYYYYYYY from any node: java.io.IOException: No live nodes
contain current block. Will get new block locations from namenode and retry...