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From "Mahadev konar (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-489) Seperating user logs from system logs in map reduce
Date Tue, 29 Aug 2006 21:35:23 GMT
    [ http://issues.apache.org/jira/browse/HADOOP-489?page=comments#action_12431373 ] 
Mahadev konar commented on HADOOP-489:

Adding doug's comments on hadoop-dev

Arkady Borkovsky wrote:
> With these point in mind, solution (3) does not look attractive -- at 
> least as long as the tools for immediate access to such logs are perfect.

Currently we have HTTP access to log files as each line is logged.  Is that not immediate

> I like solution (2).   Concatenation is separate issue -- the important 
> thing is immediate availability.

DFS files are not visible until they are closed.  So logs in DFS would not generally be viewable
until the task is complete.

> Maybe solution (2) be modified so that the messages from all tasks go 
> to the single DFS files -- each line of the logs prefixed with task ID 
> and time stamp?

That would create an i/o bottleneck.  We don't want to be log-bound.

I really think we want to continue to log to a local file, and then provide easy access to
this over HTTP.  What's needed are tools to: (a) display fatal errors as they happen; (b)
use logs as MapReduce input, so that they can, if desired, be efficiently written to DFS for
retrospective analysis; (c) display all messages as they occur (tail -f).  I have reservations
about (c), since reading logs from 1000 nodes blended together in a single stream is not easy.
 Rather, I think polling for the last N lines or new lines since last poll (whichever is
smaller) would be more useful, since you'd get some context with each entry.

> 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: 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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