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MapReduce >> mail # user >> Re: produce a large sequencefile (1TB)


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Re: produce a large sequencefile (1TB)
Unfortunately given the way Reducers work today you wouldn't be able
to do this. They are designed to fetch all data before the merge, sort
and process it through the reducer implementation. For that to work,
as you've yourself deduced, you will need as much space locally
available.

What you could do however, is perhaps just run a Map-only job, let it
produce smaller files, then run a non-MR java app that reads them all
one by one, and appends to a single HDFS SequenceFile. This is like a
reducer, but minus a local sort phase. If the sort is important to you
as well, then your tweaking will have to go further into using
multiple reducers with Total Order Partitioning, and then running this
external java app.

On Tue, Aug 20, 2013 at 8:25 AM, Bing Jiang <[EMAIL PROTECTED]> wrote:
> Hi Jerry,
>
> I think whether it is acceptable to set multiple reducers to generate more
> MapFile(IndexFile, DataFile)s.
>
> I want to know the real difficulties of multiply reducer to post-processing.
> Maybe there are some questions about app?
>
>
>
> 2013/8/20 Jerry Lam <[EMAIL PROTECTED]>
>>
>> Hi Bing,
>>
>> you are correct. The local storage does not have enough capacity to hold
>> the temporary files generated by the mappers. Since we want a single
>> sequence file at the end, we are forced to use 1 reducer.
>>
>> The use case is that we want to generate an index for the 1TB sequence
>> file that we can randomly access each row in the sequence file. In practice,
>> this is simply a MapFile.
>>
>> Any idea how to resolve this dilemma is greatly appreciated.
>>
>> Jerry
>>
>>
>>
>> On Mon, Aug 19, 2013 at 8:14 PM, Bing Jiang <[EMAIL PROTECTED]>
>> wrote:
>>>
>>> hi,Jerry.
>>> I think you are worrying about the volumn of mapreduce local file, but
>>> would  you give us more details about your apps.
>>>
>>> On Aug 20, 2013 6:09 AM, "Jerry Lam" <[EMAIL PROTECTED]> wrote:
>>>>
>>>> Hi Hadoop users and developers,
>>>>
>>>> I have a use case that I need produce a large sequence file of 1 TB in
>>>> size when each datanode has  200GB of storage but I have 30 datanodes.
>>>>
>>>> The problem is that no single reducer can hold 1TB of data during the
>>>> reduce phase to generate a single sequence file even I use aggressive
>>>> compression. Any datanode will run out of space since this is a single
>>>> reducer job.
>>>>
>>>> Any comment and help is appreciated.
>>>>
>>>> Jerry
>>
>>
>
>
>
> --
> Bing Jiang
> Tel:(86)134-2619-1361
> weibo: http://weibo.com/jiangbinglover
> BLOG: www.binospace.com
> BLOG: http://blog.sina.com.cn/jiangbinglover
> Focus on distributed computing, HDFS/HBase

--
Harsh J
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