hadoop-common-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Steve Loughran <ste...@apache.org>
Subject Re: parallel cat
Date Thu, 07 Jul 2011 09:35:39 GMT
On 07/07/11 08:22, Rita wrote:
> Thanks Steve. This is exactly what I was looking for. Unfortunately, I don
> see any example code for the implementation.
>

No. I think I have access to russ's source somewhere, but there'd be 
paperwork in getting it released. Russ said it wasn't too hard to do, he 
just had to patch the DFS client to offer up the entire list of block 
locations to the client, and let the client program make the decision. 
If you discussed this on the hdfs-dev list (via a JIRA), you may be able 
to get a patch for this accepted, though you have to do the code and 
tests yourself.

>
> On Wed, Jul 6, 2011 at 7:35 AM, Steve Loughran<stevel@apache.org>  wrote:
>
>> On 06/07/11 11:08, Rita wrote:
>>
>>> I have many large files ranging from 2gb to 800gb and I use hadoop fs -cat
>>> a
>>> lot to pipe to various programs.
>>>
>>> I was wondering if its possible to prefetch the data for clients with more
>>> bandwidth. Most of my clients have 10g interface and datanodes are 1g.
>>>
>>> I was thinking, prefetch x blocks (even though it will cost extra memory)
>>> while reading block y. After block y is read, read the prefetched blocked
>>> and then throw it away.
>>>
>>> It should be used like this:
>>>
>>>
>>> export PREFETCH_BLOCKS=2 #default would be 1
>>> hadoop fs -pcat hdfs://namenode/verylarge file | program
>>>
>>> Any thoughts?
>>>
>>>
>> Look at Russ Perry's work on doing very fast fetches from an HDFS filestore
>> http://www.hpl.hp.com/**techreports/2009/HPL-2009-345.**pdf<http://www.hpl.hp.com/techreports/2009/HPL-2009-345.pdf>
>>
>> Here the DFS client got some extra data on where every copy of every block
>> was, and the client decided which machine to fetch it from. This made the
>> best use of the entire cluster, by keeping each datanode busy.
>>
>>
>> -steve
>>
>
>
>


Mime
View raw message