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From Ryan Rosario <uclamath...@gmail.com>
Subject Re: Streaming ignoring stderr output
Date Mon, 26 Oct 2009 16:06:01 GMT
Thanks. I think that I may have tripped on some sort of bug.
Unfortunately, I do not know how to reproduce it and am a bit scared
to try to reproduce it.

I got this to work. I changed the following things, and now my job
completes successfully with stderr written to the logs as output
occurs. What was happening before was that no output was being written
to the stderr logs until a map task completely finished.

-- used print >> sys.stderr, "blah blah" instead of
sys.stderr.write("blah blah")
-- used the reporter:  print >> sys.stderr, "reporter:status:My status message"
-- used only one large input file, rather than splitting the file into
n files. I thought that was required so I could force n mappers, but
apparently not.

I am not sure which one of the above solved the problem. Using
sys.stderr.write() without the reporting format worked for some time.
I don't know why.

- Ryan

On Mon, Oct 26, 2009 at 8:03 AM, Koji Noguchi <knoguchi@yahoo-inc.com> wrote:
> This doesn't solve your stderr/stdout problem, but you can always set the
> timeout to be a bigger value if necessary.
> -Dmapred.task.timeout=______ (in milliseconds)
> Koji
> On 10/25/09 12:00 PM, "Ryan Rosario" <uclamathguy@gmail.com> wrote:
>> I am using a Python script as a mapper for a Hadoop Streaming (hadoop
>> 0.20.0) job, with reducer NONE. My jobs keep getting killed with "task
>> failed to respond after 600 seconds." I tried sending a heartbeat
>> every minute to stderr using sys.stderr.write in my mapper, but
>> nothing is being output to stderr either on disk (in
>> logs/userlogs/...) or in the web UI. stdout is not even recorded.
>> This also means I have no way of knowing what my tasks are doing at
>> any given moment except to look at the counts produced in syslog.
>> I got it to work once, but have not had any luck since. Any
>> suggestions of things to look at as to why I am not able to get any
>> output? Help is greatly appreciated.
>> - Ryan


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