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MapReduce >> mail # user >> partition as block?


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Jay Vyas 2013-04-30, 18:46
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Mohammad Tariq 2013-04-30, 18:56
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Re: partition as block?
What do you mean "increasing the size"?  Im talking more about increasing the number of partitions... Which actually decreases individual file size.

On Apr 30, 2013, at 4:09 PM, Mohammad Tariq <[EMAIL PROTECTED]> wrote:

> Increasing the size can help us to an extent, but increasing it further might cause problems during copy and shuffle. If the partitions are too big to be held in the memory, we'll end up with disk based shuffle which is gonna be slower than RAM based shuffle, thus delaying the entire reduce phase. Furthermore N/W might get overwhelmed.
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> I think keeping it "considerably" high will definitely give you some boost. But it'll require a high level tinkering.
>
> Warm Regards,
> Tariq
> https://mtariq.jux.com/
> cloudfront.blogspot.com
>
>
> On Wed, May 1, 2013 at 1:29 AM, Jay Vyas <[EMAIL PROTECTED]> wrote:
>> Yes it is a problem at the first stage.  What I'm wondering, though, is wether the intermediate results - which happen after the mapper phase - can be optimized.
>>
>>
>> On Tue, Apr 30, 2013 at 3:38 PM, Mohammad Tariq <[EMAIL PROTECTED]> wrote:
>>> Hmmm. I was actually thinking about the very first step. How are you going to create the maps. Suppose you are on a block-less filesystem and you have a custom Format that is going to give you the splits dynamically. This mean that you are going to store the file as a whole and create the splits as you continue to read the file. Wouldn't it be a bottleneck from 'disk' point of view??Are you not going away from the distributed paradigm??
>>>
>>> Am I taking it in the correct way. Please correct me if I am getting it wrong.
>>>
>>> Warm Regards,
>>> Tariq
>>> https://mtariq.jux.com/
>>> cloudfront.blogspot.com
>>>
>>>
>>> On Wed, May 1, 2013 at 12:34 AM, Jay Vyas <[EMAIL PROTECTED]> wrote:
>>>> Well, to be more clear, I'm wondering how hadoop-mapreduce can be optimized in a block-less filesystem... And am thinking about application tier ways to simulate blocks - i.e. by making the granularity of partitions smaller.
>>>>
>>>> Wondering, if there is a way to hack an increased numbers of partitions as a mechanism to simulate blocks - or wether this is just a bad idea altogether :)
>>>>
>>>>
>>>>
>>>>
>>>> On Tue, Apr 30, 2013 at 2:56 PM, Mohammad Tariq <[EMAIL PROTECTED]> wrote:
>>>>> Hello Jay,
>>>>>
>>>>>     What are you going to do in your custom InputFormat and partitioner?Is your InputFormat is going to create larger splits which will overlap with larger blocks?If that is the case, IMHO, then you are going to reduce the no. of mappers thus reducing the parallelism. Also, much larger block size will put extra overhead when it comes to disk I/O.
>>>>>
>>>>> Warm Regards,
>>>>> Tariq
>>>>> https://mtariq.jux.com/
>>>>> cloudfront.blogspot.com
>>>>>
>>>>>
>>>>> On Wed, May 1, 2013 at 12:16 AM, Jay Vyas <[EMAIL PROTECTED]> wrote:
>>>>>> Hi guys:
>>>>>>
>>>>>> Im wondering - if I'm running mapreduce jobs on a cluster with large block sizes - can i increase performance with either:
>>>>>>
>>>>>> 1) A custom FileInputFormat
>>>>>>
>>>>>> 2) A custom partitioner
>>>>>>
>>>>>> 3) -DnumReducers
>>>>>>
>>>>>> Clearly, (3) will be an issue due to the fact that it might overload tasks and network traffic... but maybe (1) or (2) will be a precise way to "use" partitions as a "poor mans" block.  
>>>>>>
>>>>>> Just a thought - not sure if anyone has tried (1) or (2) before in order to simulate blocks and increase locality by utilizing the partition API.
>>>>>>
>>>>>> --
>>>>>> Jay Vyas
>>>>>> http://jayunit100.blogspot.com
>>>>
>>>>
>>>>
>>>> --
>>>> Jay Vyas
>>>> http://jayunit100.blogspot.com
>>
>>
>>
>> --
>> Jay Vyas
>> http://jayunit100.blogspot.com
>
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB