Seperating user logs from system logs in map reduce
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Key: HADOOP-489
URL: http://issues.apache.org/jira/browse/HADOOP-489
Project: Hadoop
Issue Type: Improvement
Components: mapred
Reporter: Mahadev konar
Assigned To: Mahadev konar
Priority: Minor
Currently the user logs are a part of system logs in mapreduce. Anything logged
by the user is logged into the tasktracker log files. This create two issues-
1) The system log files get cluttered with user output. If the user outputs a
large amount of logs, the system logs need to be cleaned up pretty often.
2) For the user, it is difficult to get to each of the machines and look for
the logs his/her job might have generated.
I am proposing three solutions to the problem. All of them have issues with it -
Solution 1.
Output the user logs on the user screen as part of the job submission process.
Merits-
This will prevent users from printing large amount of logs and the user can get
runtime feedback on what is wrong with his/her job.
Issues -
This proposal will use the framework bandwidth while running jobs for the user.
The user logs will need to pass from the tasks to the tasktrackers, from the
tasktrackers to the jobtrackers and then from the jobtrackers to the jobclient
using a lot of framework bandwidth if the user is printing out too much data.
Solution 2.
Output the user logs onto a dfs directory and then concatenate these files.
Each task can create a file for the output in the log direcotyr for a given
user and jobid.
Issues -
This will create a huge amount of small files in DFS which later can be
concatenated into a single file. Also there is this issue that who would
concatenate these files into a single file? This could be done by the framework
(jobtracker) as part of the cleanup for the jobs - might stress the jobtracker.
Solution 3.
Put the user logs into a seperate user log file in the log directory on each
tasktrackers. We can provide some tools to query these local log files. We
could have commands like for jobid j and for taskid t get me the user log
output. These tools could run as a seperate map reduce program with each map
grepping the user log files and a single recude aggregating these logs in to a
single dfs file.
Issues-
This does sound like more work for the user. Also, the output might not be
complete since a tasktracker might have went down after it ran the job.
Any thoughts?
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