Hive 执行命令卡在Connecting to ResourceManager at Master:8032 解决方法
作者:
dave
在Hadoop 中执行命令,结果卡住不动:
hive> select count(1) from employees;
Query ID = hadoop_20190309205753_9eac66d2-7887-475d-ac86-a7cba452e70c
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
set mapreduce.job.reduces=<number>
2019-03-09 20:57:58,132 INFO [6be0ea3b-ca7b-47d2-9b30-77fbe929d85a main] client.RMProxy: Connecting to ResourceManager at Master:8032
2019-03-09 20:57:58,546 INFO [6be0ea3b-ca7b-47d2-9b30-77fbe929d85a main] client.RMProxy: Connecting to ResourceManager at Master:8032
Interrupting... Be patient, this might take some time.
Press Ctrl+C again to kill JVM
Exiting the JVM
这里是因为资源管理进程没有启动,查看进程信息:
[hadoop@hadoopMaster ~]$ jps
13970 QuorumPeerMain
21141 SecondaryNameNode
21479 Jps
20907 NameNode
[hadoop@hadoopMaster ~]$
确实没有启动,我这里是因为之前修改了主机名,而没有修改yarn-site.xml中对应的名称导致的,修改成正确的主机名后重启yarn,恢复正常:
[hadoop@hadoopMaster logs]$ pwd
/home/hadoop/hadoop/logs
[hadoop@hadoopMaster logs]$ ls
fairscheduler-statedump.log hadoop-hadoop-resourcemanager-hadoopMaster.out hadoop-hadoop-secondarynamenode-hadoopMaster.out
hadoop-hadoop-namenode-hadoopMaster.log hadoop-hadoop-resourcemanager-hadoopMaster.out.1 hadoop-hadoop-secondarynamenode-hadoopMaster.out.1
hadoop-hadoop-namenode-hadoopMaster.out
[hadoop@hadoopMaster ~]$ jps
13970 QuorumPeerMain
23522 NameNode
24290 RunJar
23988 ResourceManager
24521 Jps
23757 SecondaryNameNode
[hadoop@hadoopMaster ~]$
hive> select count(1) from employees;
Query ID = hadoop_20190309212230_d945dafb-311b-4b04-8e0b-7e14671a71e7
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
set mapreduce.job.reduces=<number>
2019-03-09 21:22:35,564 INFO [11ef99e0-fe20-400e-87b6-1006d834fa31 main] client.RMProxy: Connecting to ResourceManager at hadoopMaster/192.168.56.100:8032
2019-03-09 21:22:35,917 INFO [11ef99e0-fe20-400e-87b6-1006d834fa31 main] client.RMProxy: Connecting to ResourceManager at hadoopMaster/192.168.56.100:8032
Starting Job = job_1552137405153_0002, Tracking URL = http://hadoopMaster:8088/proxy/application_1552137405153_0002/
Kill Command = /home/hadoop/hadoop/bin/mapred job -kill job_1552137405153_0002
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2019-03-09 21:22:47,562 Stage-1 map = 0%, reduce = 0%
2019-03-09 21:22:53,935 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.27 sec
2019-03-09 21:23:01,275 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 4.6 sec
MapReduce Total cumulative CPU time: 4 seconds 600 msec
Ended Job = job_1552137405153_0002
MapReduce Jobs Launched:
Stage-Stage-1: Map: 1 Reduce: 1 Cumulative CPU: 4.6 sec HDFS Read: 21015 HDFS Write: 103 SUCCESS
Total MapReduce CPU Time Spent: 4 seconds 600 msec
OK
424
Time taken: 31.697 seconds, Fetched: 1 row(s)
hive>
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