Hello guys,
My 2 cents :
Actually no. of mappers is primarily governed by the no. of InputSplits
created by the InputFormat you are using and the no. of reducers by the no.
of partitions you get after the map phase. Having said that, you should
also keep the no of slots, available per slave, in mind, along with the
available memory. But as a general rule you could use this approach :
Take the no. of virtual CPUs*.75 and that's the no. of slots you can
configure. For example, if you have 12 physical cores (or 24 virtual
cores), you would have (24*.75)=18 slots. Now, based on your requirement
you could choose how many mappers and reducers you want to use. With 18 MR
slots, you could have 9 mappers and 9 reducers or 12 mappers and 9 reducers
or whatever you think is OK with you.
I don't know if it ,makes much sense, but it helps me pretty decently.
Warm Regards,
Tariq
cloudfront.blogspot.com
On Sat, May 11, 2013 at 8:57 PM, Rahul Bhattacharjee <
rahul.rec....@gmail.com> wrote:
> Hi,
>
> I am also new to Hadoop world , here is my take on your question , if
> there is something missing then others would surely correct that.
>
> For per-YARN , the slots are fixed and computed based on the crunching
> capacity of the datanode hardware , once the slots per data node is
> ascertained , they are divided into Map and reducer slots and that goes
> into the config files and remain fixed , until changed.In YARN , its
> decided at runtime based on the kind of requirement of particular task.Its
> very much possible that a datanode at certain point of time running 10
> tasks and another similar datanode is only running 4 tasks.
>
> Coming to your question. Based of the data set size , block size of dfs
> and input formater , the number of map tasks are decided , generally for
> file based inputformats its one mapper per data block , however there are
> way to change this using configuration settings.Reduce tasks are set using
> job configuration.
>
> General rule as I have read from various documents is that Mappers should
> run atleast a minute , so you can run a sample to find out a good size of
> data block which would make you mapper run more than a minute. Now it again
> depends on your SLA , in case you are not looking for a very small SLA you
> can choose to run less mappers at the expense of higher runtime.
>
> But again its all theory , not sure how these things are handled in actual
> prod clusters.
>
> HTH,
>
>
>
> Thanks,
> Rahul
>
>
> On Sat, May 11, 2013 at 8:02 PM, Shashidhar Rao <
> raoshashidhar...@gmail.com> wrote:
>
>> Hi Users,
>>
>> I am new to Hadoop and confused about task slots in a cluster. How would
>> I know how many task slots would be required for a job. Is there any
>> empirical formula or on what basis should I set the number of task slots.
>>
>> Advanced Thanks
>>
>
>
