I think David's solution is viable, but don't use a local variable as a counter
in step 4, use a COUNTER object to count the error record, the COUNTER object
can work globally.
At 2011-11-16 03:08:45,"Mapred Learn" <mapred.le...@gmail.com> wrote:
Thanks David for a step-by-step response but this makes error threshold, a per
mapper threshold. Is there a way to make it per job so that all mappers share
this value and increment it as a shared counter ?
On Tue, Nov 15, 2011 at 8:12 AM, David Rosenstrauch <dar...@darose.net> wrote:
On 11/14/2011 06:06 PM, Mapred Learn wrote:
Hi,
I have a use case where I want to pass a threshold value to a map-reduce
job. For eg: error records=10.
I want map-reduce job to fail if total count of error_records in the job
i.e. all mappers, is reached.
How can I implement this considering that each mapper would be processing
some part of the input data ?
Thanks,
-JJ
1) Pass in the threshold value as configuration value of the M/R job. (i.e.,
job.getConfiguration().setInt("error_threshold", 10) )
2) Make your mappers implement the Configurable interface. This will ensure
that every mapper gets passed a copy of the config object.
3) When you implement the setConf() method in your mapper (which Configurable
will force you to do), retrieve the threshold value from the config and save it
in an instance variable in the mapper. (i.e., int errorThreshold =
conf.getInt("error_threshold") )
4) In the mapper, when an error record occurs, increment a counter and then
check if the counter value exceeds the threshold. If so, throw an exception.
(e.g., if (++numErrors >= errorThreshold) throw new RuntimeException("Too many
errors") )
The exception will kill the mapper. Hadoop will attempt to re-run it, but
subsequent attempts will also fail for the same reason, and eventually the
entire job will fail.
HTH,
DR
