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From nutch buddy <nutch.bu...@gmail.com>
Subject Re: why is num of map tasks gets overridden?
Date Thu, 23 Aug 2012 11:12:14 GMT
how do I adjust number of slots per node?
and also,  is the parameter maperd.tasktracker.map.tasks.maximum relevant
here?

thanks

On Wed, Aug 22, 2012 at 9:23 AM, Bertrand Dechoux <dechouxb@gmail.com>wrote:

> 3) Similarly to 2, you could consider multithreading. So in each physical
> node you would only to have the equivalent in memory of what is required
> for a map while having the processing power of many. But it will depend on
> your context ie how you are using the memory.
>
> But 1) is really the key indeed : <number of slots per physical node> *
> <maximum memory per slot> shouldn't be superior to what is available in
> your physical node.
>
> Regards
>
> Bertrand
>
>
> On Wed, Aug 22, 2012 at 8:03 AM, Bejoy KS <bejoy.hadoop@gmail.com> wrote:
>
>> **
>> Hi
>>
>> There are two options I can think of now
>>
>> 1) If all your jobs are memory intensive I'd recommend you to adjust your
>> task slots per node accordingly
>> 2) If only a few jobs are memory intensive, you can think of each map
>> task processing lesser volume of data. For that set mapred.max.splitsize to
>> the maximum data chuck a map task can process with your current memory
>> constrain.
>> Regards
>> Bejoy KS
>>
>> Sent from handheld, please excuse typos.
>> ------------------------------
>> *From: * nutch buddy <nutch.buddy@gmail.com>
>> *Date: *Wed, 22 Aug 2012 08:57:31 +0300
>> *To: *<user@hadoop.apache.org>
>> *ReplyTo: * user@hadoop.apache.org
>> *Subject: *Re: why is num of map tasks gets overridden?
>>
>> So what can I do If I have a given input, and my job needs a lot of
>> memroy per map task?
>> I can't control the amount of map tasks, and my total memory per machine
>> is limited - I'll eventaully get each machine's memory full.
>>
>> On Tue, Aug 21, 2012 at 3:52 PM, Bertrand Dechoux <dechouxb@gmail.com>wrote:
>>
>>> Actually controlling the number of maps is subtle. The mapred.map.tasks
>>>> parameter is just a hint to the InputFormat for the number of maps. The
>>>> default InputFormat behavior is to split the total number of bytes into the
>>>> right number of fragments. However, in the default case the DFS block size
>>>> of the input files is treated as an upper bound for input splits. A lower
>>>> bound on the split size can be set via mapred.min.split.size. Thus, if you
>>>> expect 10TB of input data and have 128MB DFS blocks, you'll end up with 82k
>>>> maps, unless your mapred.map.tasks is even larger. Ultimately the
>>>> InputFormat<http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/mapred/InputFormat.html>determines
the number of maps.
>>>>
>>>
>>> http://wiki.apache.org/hadoop/HowManyMapsAndReduces
>>>
>>> Bertrand
>>>
>>>
>>> On Tue, Aug 21, 2012 at 2:19 PM, nutch buddy <nutch.buddy@gmail.com>wrote:
>>>
>>>> I configure a job in hadoop ,set the number of map tasks in the code to
>>>> 8.
>>>>
>>>> Then I run the job and it gets 152 map tasks. Can't get why its being
>>>> overriden and whhere it get 152 from.
>>>>
>>>> The mapred-site.xml has 24 as mapred.map.tasks.
>>>>
>>>> any idea?
>>>>
>>>
>>>
>>>
>>> --
>>> Bertrand Dechoux
>>>
>>
>>
>
>
> --
> Bertrand Dechoux
>

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