I have set up a pseudo distributed mode cluster setup. The FIFO scheduler got stuck somehow in between and therefore a lot of jobs got piled up which I had scheduler through cron. Now, when I restarted YARN resourcemanager it gets stuck after a while and the jobs keep piling up.
Is there a way I can clear the whole queue. Or, is it that my complete understanding of hadoop scheduling is somewhere flawed. Please help.
If you're trying to kill all the jobs in your queue, you can use this shell script:
$HADOOP_HOME/bin/hadoop job -list | awk ' { system("$HADOOP_HOME/bin/hadoop job -kill " $1) } '
Related
I recently attempted to do an export of a table from an HBase instance using a 10 data node Hadoop cluster. The command line looked like the following:
nohup hbase org.apache.hadoop.hbase.mapreduce.Export documents /export/documents 10 > ~/documents_export.out &
As you can see, I nohup the process so it wouldn't prematurely die when my SSH session closed, and I put the whole thing in the background. To capture the output, I directed it to a file.
As expected, the process started to run and in fact ran for several hours before the output mysteriously stopped in the file I was outputting to. It stopped at about 31% through the mapping phase of the mapreduce job being run. However, per Hadoop, the mapreduce job itself was still going and in fact was working to completion the next morning.
So, my question is why did output stop going to my log file? My best guess is that the parent HBase process I invoked exited normally when it was done with the initial setup for the mapreduce job involved in the export.
I ran the following command on my local filesystem:
hadoop fs -copyToLocal <HDFS Path>
But, in the middle of the task (after hitting the command in terminal and before the command completes it's task), I want to cancel the copy. How can I do this ?
Also, is -copyToLocal executed as a MR job internally ? Can someone point me to a reference.
Thanks.
It uses the FileSystem API to stream & copy the file to local. There is no MR.
You could find the process on the machine & kill the process. It is usually a JVM process which gets invoked.
if you are using Nohup and/or & to perform the process you will get the job status by searching CopyToLocal in ps -eaf action, and if you are using normal command execution, you can use ctrl+z or ctrl+c. these will kill the process.
In Both case the dump and temp location which all create remains there, so once killing the process you have to clear the dump/temp dump to perform the same process again.
It will not create any MR Job,
How do we interrupt pig dump command (EDIT: when it has completed the MapReduce jobs and is now just displaying the result on grunt shell) without exiting the grunt shell?
Sometimes, if we dump a HUGE file by mistake, it goes on forever!
I know we can use CTRL+C to stop it but it also quits the grunt shell and then we have to write all the commands again.
We can execute the following command in the grunt shell
kill jobid
We can find the job’s ID by looking at Hadoop’s JobTracker GUI, which lists all jobs currently running on the cluster. Note that this command kills a particular MapReduce job. If the Pig job contains other MapReduce jobs that do not depend on the killed MapReduce job, these jobs will still continue. If you want to kill all of the MapReduce jobs associated with a particular Pig job, it is best to terminate the process running Pig using CTRL+C, and then use this command to kill any MapReduce jobs that are still running.
I want to kill all my hadoop jobs automatically when my code encounters an unhandled exception. I am wondering what is the best practice to do it?
Thanks
Depending on the version, do:
version <2.3.0
Kill a hadoop job:
hadoop job -kill $jobId
You can get a list of all jobId's doing:
hadoop job -list
version >=2.3.0
Kill a hadoop job:
yarn application -kill $ApplicationId
You can get a list of all ApplicationId's doing:
yarn application -list
Use of folloing command is depreciated
hadoop job -list
hadoop job -kill $jobId
consider using
mapred job -list
mapred job -kill $jobId
Run list to show all the jobs, then use the jobID/applicationID in the appropriate command.
Kill mapred jobs:
mapred job -list
mapred job -kill <jobId>
Kill yarn jobs:
yarn application -list
yarn application -kill <ApplicationId>
An unhandled exception will (assuming it's repeatable like bad data as opposed to read errors from a particular data node) eventually fail the job anyway.
You can configure the maximum number of times a particular map or reduce task can fail before the entire job fails through the following properties:
mapred.map.max.attempts - The maximum number of attempts per map task. In other words, framework will try to execute a map task these many number of times before giving up on it.
mapred.reduce.max.attempts - Same as above, but for reduce tasks
If you want to fail the job out at the first failure, set this value from its default of 4 to 1.
Simply forcefully kill the process ID, the hadoop job will also be killed automatically . Use this command:
kill -9 <process_id>
eg: process ID no: 4040 namenode
username#hostname:~$ kill -9 4040
Use below command to kill all jobs running on yarn.
For accepted jobs use below command.
for x in $(yarn application -list -appStates ACCEPTED | awk 'NR > 2 { print $1 }'); do yarn application -kill $x; done
For running, jobs use the below command.
for x in $(yarn application -list -appStates RUNNING | awk 'NR > 2 { print $1 }'); do yarn application -kill $x; done
am new to hadoop and a small help is required.
Suppose if i ran the job in background using shell scripting, how do i know whether the job is completed or not. The reason am asking is, once the job is completed my script has to move output file to some other location. How can i check whether job completed or outfile exists or not using hdfs.
Thanks
MRK
You need to be careful in the way you are detecting the job is done in this way, because there might be output before your job is completely finished.
To answer your direct question, to test for existence I typically do hadoop fs -ls $output | wc -l and then make sure the number is greater than 0.
My suggestion is you use && to tack on the move:
hadoop ... myjob.jar ... && hadoop fs -mv $output $new_output &
This will complete the job, and then perform the move afterwards.
You can use JobConf.setJobEndNotificationURI() to get notified when the job gets completed.
I think you can also check for the pid of the process that started the Hadoop job using the ps command.