HIVE报错:ERROR:FAILED:Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapReduce
执行Hive卡死或报错:INFO : Query ID = hive_20190910180101_f63579a5-ee9a-4ab3-87a7-2c9fb7c1a7abINFO : Total jobs = 5INFO : Starting task [Stage-38:CONDITIONAL] in serial modeINFO : Stage-1 is selecte...
执行Hive卡死或报错:
INFO : Query ID = hive_20190910180101_f63579a5-ee9a-4ab3-87a7-2c9fb7c1a7ab
INFO : Total jobs = 5
INFO : Starting task [Stage-38:CONDITIONAL] in serial mode
INFO : Stage-1 is selected by condition resolver.
INFO : Launching Job 1 out of 5
INFO : Starting task [Stage-1:MAPRED] in serial mode
INFO : Number of reduce tasks not specified. Defaulting to jobconf value of: 2
INFO : In order to change the average load for a reducer (in bytes):
INFO : set hive.exec.reducers.bytes.per.reducer=<number>
INFO : In order to limit the maximum number of reducers:
INFO : set hive.exec.reducers.max=<number>
INFO : In order to set a constant number of reducers:
INFO : set mapreduce.job.reduces=<number>
INFO : number of splits:2
INFO : Submitting tokens for job: job_1567761414821_0189
INFO : The url to track the job: http://master:7077/proxy/application_1567761414821_0189/
INFO : Starting Job = job_1567761414821_0189, Tracking URL = http://master:7077/proxy/application_1567761414821_0189/
INFO : Kill Command = /opt/cloudera/parcels/CDH-5.12.1-1.cdh5.12.1.p0.3/lib/hadoop/bin/hadoop job -kill job_1567761414821_0189
执行到这里卡死,时间长了报错:
INFO : Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 2
INFO : 2019-09-10 18:01:39,431 Stage-1 map = 0%, reduce = 0%
INFO : 2019-09-10 18:01:47,810 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 5.99 sec
INFO : 2019-09-10 18:02:06,319 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 5.99 sec
INFO : MapReduce Total cumulative CPU time: 5 seconds 990 msec
ERROR : Ended Job = job_1567761414821_0189 with errors
ERROR : FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask
INFO : MapReduce Jobs Launched:
INFO : Stage-Stage-1: Map: 2 Reduce: 2 Cumulative CPU: 5.99 sec HDFS Read: 19557391 HDFS Write: 0 FAIL
INFO : Total MapReduce CPU Time Spent: 5 seconds 990 msec
INFO : Completed executing command(queryId=hive_20190910180101_f63579a5-ee9a-4ab3-87a7-2c9fb7c1a7ab); Time taken: 32.908 seconds
Error: Error while processing statement: FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask (state=08S01,code=2)
可以看到Kylin都卡了几百分钟
很可是因为没有资源的原因:
首先检查Yarn资源:
可以看到使用的默认队列 以及三台节点加起来分配8.6G. 但是我每台节点分配了32G内存
还有就是,我划分了两个队列,每个队列50%资源。
没有资源,所以两种方法,第一个就是一个一个来试一下,或者加大资源。
yarn的资源模型 yarn划分队列配置:
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