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From "Owen O'Malley (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-489) Seperating user logs from system logs in map reduce
Date Tue, 07 Nov 2006 19:48:54 GMT
    [ http://issues.apache.org/jira/browse/HADOOP-489?page=comments#action_12447912 ] 
            
Owen O'Malley commented on HADOOP-489:
--------------------------------------

#5 above should have been TaskLog.LOG_DIR should be a File instead of a String.

Also, if the user output is less than 4k, you get a warning about potential pruning, if you
ask for the last 4k.

> Seperating user logs from system logs in map reduce
> ---------------------------------------------------
>
>                 Key: HADOOP-489
>                 URL: http://issues.apache.org/jira/browse/HADOOP-489
>             Project: Hadoop
>          Issue Type: Improvement
>          Components: mapred
>            Reporter: Mahadev konar
>         Assigned To: Arun C Murthy
>            Priority: Minor
>         Attachments: HADOOP-489_20061019.patch, HADOOP-489_20061101.patch, HADOOP-489_20061102.patch,
HADOOP-489_20061107.patch
>
>
> 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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