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Posted to common-user@hadoop.apache.org by parnab kumar <pa...@gmail.com> on 2014/08/18 18:55:51 UTC
ignoring map task failure
Hi All,
I am running a job where there are between 1300-1400 map tasks. Some
map task fails due to some error. When 4 such maps fail the job naturally
gets killed. How to ignore the failed tasks and go around executing the
other map tasks. I am okay with loosing some data for the failed tasks.
Thanks,
Parnab
Re: ignoring map task failure
Posted by Tsuyoshi OZAWA <oz...@gmail.com>.
Hi,
Please check the value of mapreduce.map.maxattempts and
mapreduce.reduce.maxattempts. If you'd like to ignore the error only
in specific jobs, it's useful to use -D option to change the
configuration as follows:
bin/hadoop jar job.jar -Dmapreduce.map.maxattempts=10
Thanks,
- Tsuyoshi
On Tue, Aug 19, 2014 at 2:57 AM, Susheel Kumar Gadalay
<sk...@gmail.com> wrote:
> Check the parameter yarn.app.mapreduce.client.max-retries.
>
> On 8/18/14, parnab kumar <pa...@gmail.com> wrote:
>> Hi All,
>>
>> I am running a job where there are between 1300-1400 map tasks. Some
>> map task fails due to some error. When 4 such maps fail the job naturally
>> gets killed. How to ignore the failed tasks and go around executing the
>> other map tasks. I am okay with loosing some data for the failed tasks.
>>
>> Thanks,
>> Parnab
>>
--
- Tsuyoshi
Re: ignoring map task failure
Posted by Tsuyoshi OZAWA <oz...@gmail.com>.
Hi,
Please check the value of mapreduce.map.maxattempts and
mapreduce.reduce.maxattempts. If you'd like to ignore the error only
in specific jobs, it's useful to use -D option to change the
configuration as follows:
bin/hadoop jar job.jar -Dmapreduce.map.maxattempts=10
Thanks,
- Tsuyoshi
On Tue, Aug 19, 2014 at 2:57 AM, Susheel Kumar Gadalay
<sk...@gmail.com> wrote:
> Check the parameter yarn.app.mapreduce.client.max-retries.
>
> On 8/18/14, parnab kumar <pa...@gmail.com> wrote:
>> Hi All,
>>
>> I am running a job where there are between 1300-1400 map tasks. Some
>> map task fails due to some error. When 4 such maps fail the job naturally
>> gets killed. How to ignore the failed tasks and go around executing the
>> other map tasks. I am okay with loosing some data for the failed tasks.
>>
>> Thanks,
>> Parnab
>>
--
- Tsuyoshi
Re: ignoring map task failure
Posted by Tsuyoshi OZAWA <oz...@gmail.com>.
Hi,
Please check the value of mapreduce.map.maxattempts and
mapreduce.reduce.maxattempts. If you'd like to ignore the error only
in specific jobs, it's useful to use -D option to change the
configuration as follows:
bin/hadoop jar job.jar -Dmapreduce.map.maxattempts=10
Thanks,
- Tsuyoshi
On Tue, Aug 19, 2014 at 2:57 AM, Susheel Kumar Gadalay
<sk...@gmail.com> wrote:
> Check the parameter yarn.app.mapreduce.client.max-retries.
>
> On 8/18/14, parnab kumar <pa...@gmail.com> wrote:
>> Hi All,
>>
>> I am running a job where there are between 1300-1400 map tasks. Some
>> map task fails due to some error. When 4 such maps fail the job naturally
>> gets killed. How to ignore the failed tasks and go around executing the
>> other map tasks. I am okay with loosing some data for the failed tasks.
>>
>> Thanks,
>> Parnab
>>
--
- Tsuyoshi
Re: ignoring map task failure
Posted by Tsuyoshi OZAWA <oz...@gmail.com>.
Hi,
Please check the value of mapreduce.map.maxattempts and
mapreduce.reduce.maxattempts. If you'd like to ignore the error only
in specific jobs, it's useful to use -D option to change the
configuration as follows:
bin/hadoop jar job.jar -Dmapreduce.map.maxattempts=10
Thanks,
- Tsuyoshi
On Tue, Aug 19, 2014 at 2:57 AM, Susheel Kumar Gadalay
<sk...@gmail.com> wrote:
> Check the parameter yarn.app.mapreduce.client.max-retries.
>
> On 8/18/14, parnab kumar <pa...@gmail.com> wrote:
>> Hi All,
>>
>> I am running a job where there are between 1300-1400 map tasks. Some
>> map task fails due to some error. When 4 such maps fail the job naturally
>> gets killed. How to ignore the failed tasks and go around executing the
>> other map tasks. I am okay with loosing some data for the failed tasks.
>>
>> Thanks,
>> Parnab
>>
--
- Tsuyoshi
Re: ignoring map task failure
Posted by Susheel Kumar Gadalay <sk...@gmail.com>.
Check the parameter yarn.app.mapreduce.client.max-retries.
On 8/18/14, parnab kumar <pa...@gmail.com> wrote:
> Hi All,
>
> I am running a job where there are between 1300-1400 map tasks. Some
> map task fails due to some error. When 4 such maps fail the job naturally
> gets killed. How to ignore the failed tasks and go around executing the
> other map tasks. I am okay with loosing some data for the failed tasks.
>
> Thanks,
> Parnab
>
Re: ignoring map task failure
Posted by Susheel Kumar Gadalay <sk...@gmail.com>.
Check the parameter yarn.app.mapreduce.client.max-retries.
On 8/18/14, parnab kumar <pa...@gmail.com> wrote:
> Hi All,
>
> I am running a job where there are between 1300-1400 map tasks. Some
> map task fails due to some error. When 4 such maps fail the job naturally
> gets killed. How to ignore the failed tasks and go around executing the
> other map tasks. I am okay with loosing some data for the failed tasks.
>
> Thanks,
> Parnab
>
Re: ignoring map task failure
Posted by Susheel Kumar Gadalay <sk...@gmail.com>.
Check the parameter yarn.app.mapreduce.client.max-retries.
On 8/18/14, parnab kumar <pa...@gmail.com> wrote:
> Hi All,
>
> I am running a job where there are between 1300-1400 map tasks. Some
> map task fails due to some error. When 4 such maps fail the job naturally
> gets killed. How to ignore the failed tasks and go around executing the
> other map tasks. I am okay with loosing some data for the failed tasks.
>
> Thanks,
> Parnab
>
Re: ignoring map task failure
Posted by Susheel Kumar Gadalay <sk...@gmail.com>.
Check the parameter yarn.app.mapreduce.client.max-retries.
On 8/18/14, parnab kumar <pa...@gmail.com> wrote:
> Hi All,
>
> I am running a job where there are between 1300-1400 map tasks. Some
> map task fails due to some error. When 4 such maps fail the job naturally
> gets killed. How to ignore the failed tasks and go around executing the
> other map tasks. I am okay with loosing some data for the failed tasks.
>
> Thanks,
> Parnab
>