I'm trying to find the best approach for logging in MapReduce jobs. I'm using slf4j with log4j appender as in my other Java applications, but since MapReduce job runs in a distributed manner across the cluster I don't know where should I set the log file location, since it is a shared cluster with limited access privileges.
Is there any standard practices for logging in MapReduce jobs, so you can easily be able to look at the logs across the cluster after the job completes?
You could use log4j which is the default logging framework that hadoop uses. So, from your MapReduce application you could do something like this:
This sample code will user log4j logger to log events to the inherited Mapper logger. All the log events will be logged to their respective task log's. You could visit the task logs from either JobTracker(MRv1)/ResourceManager(MRv2) webpage.
If you are using yarn you could access the application logs from command line using the following command:
While if you are using mapreduce v1, there is no single point of access from command line; hence you have to log into each TaskTracker and look in the configured path generally
/var/log/hadoop/userlogs/attempt_<job_id>/syslog
specified in${hadoop.log.dir}/userlogs
contains log4j output.To add to @Ashrith 's answer: you can view the individual task tracker logs via the JobTracker GUI. The running task attempts are visible by the JT Gui and you can click on any of the following: stderr, stdout, and system logs. The system logs are where you find your log4j outputs.