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From Arun C Murthy <...@yahoo-inc.com>
Subject Re: How do hadoop work in details
Date Sun, 09 Jan 2011 08:35:04 GMT

On Dec 29, 2010, at 2:43 PM, felix gao wrote:

> Hi all,
> I am trying to figure out how exactly happens inside the job.
> 1) When the jobtracker launches a task to be run, how does it impact  
> the currently running jobs if the the current running job have  
> higher, same, or lower priories using the default queue.
> 2) What if a low priority job is running that is holding all the  
> reducer slots and the mappers are halfway done and a high priority  
> job comes in took all the mappers but cannot complete but all the  
> reducer slots are taken by the low priority job?

Both 1) and 2) really depends on the scheduler you are using -  
Default, FairShare or CapacityScheduler.

With the Default scheduler, 2) is a real problem. The  
CapacityScheduler doesn't allow priorities within the same queue for  
precisely the same reason since it doesn't have preemption. I'm not  
sure if FairScheduler handles it.

> 3) when is mappers allocated on the slaves, and when is reducers  
> allocated.

Usually, reduces are allocated only after a certain percentage of maps  
are complete (5% by default). Use  
mapred.reduce.slowstart.completed.maps to control this. Look at  

> 4)Does mappers pass all the data to reducers using RPC or they write  
> their output to HDFS and the reducers pick it up.

Maps sort/combine their output and write to local-disk. The reduces  
then copy them (we call it the 'shuffle' phase) over http. The TT on  
which the map ran will serve the map's output via an embedded  
webserver. Look at ReduceTask.java and  

> 5) within a job, when and where is all the io occurs.

Typically input to map i.e. InputFormat and output of reduce i.e.  
OutputFormat. Look at MapTask.java and ReduceTask.java.

hope this helps,

> I know this seems to be a lot of low level questions , if you can  
> point me to the right place to look is should be enough.
> Thanks,
> Felix

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