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From Tharindu Mathew <mcclou...@gmail.com>
Subject Re: Extension points available for data locality
Date Tue, 21 Aug 2012 13:54:58 GMT
Yes, Micheal. You are thinking along the right lines.

I just want to understand the inner workings of this, so I can rule out
guess work when it comes to making my implementation reliable.

For example, if a node in the mysql cluster goes down and the failover node
takes over, I want to make sure Hadoop picks the failover node to pull the
data from and doesn't fail the job because the original node is unavailable.

Hence, my extensive questions on this matter. As you said, of course you
need to have the meta data to know which node holds what. Let's assume that
meta data is available.

On Tue, Aug 21, 2012 at 6:58 PM, Michael Segel <michael_segel@hotmail.com>wrote:

> Interesting....
>
> You have a cluster of MySQL which is a bit different from a single data
> source.
>
> When you say data locality, you want to run the job you mean that you want
> to launch your job and then have each mapper pull data from the local
> shard.
>
> So you have a couple of issues.
>
> 1) You will need to set up Hadoop on the same cluster.
> This is doable, you just have to account for the memory and disk on your
> system.
>
> 2) You will need to look at the HTable Input Format class.  (What's the
> difference between looking at a RS versus a shard?)
>
> 3) You will need to make sure that you have enough metadata to help
> determine where your data is located.
>
>
> Outside of that, its doable.
> Right?
>
>
> Note that since you're not running HBase, Hadoop is a bit more tolerant of
> swapping, but not by much.
>
> Good luck.
>
> On Aug 21, 2012, at 7:44 AM, Tharindu Mathew <mccloud35@gmail.com> wrote:
>
> Dino, Feng,
>
> Thanks for the options, but I guess I need to do it myself.
>
> Harsh,
>
> What you said was the initial impression I got, but I thought I need to do
> something more with the name node. Thanks for clearing that out.
>
> My guess is that this probably works by using getLocations and mapping
> this location ip (or host) with the ip (or host) of the task tracker? Is
> this correct?
>
>
> On Tue, Aug 21, 2012 at 3:14 PM, feng lu <amuseme.lu@gmail.com> wrote:
>
>> Hi Tharindu
>>
>> May you can try the Gora,The Apache Gora open source framework provides
>> an in-memory data model and persistence for big data. Gora supports
>> persisting to column stores, key value stores, document stores and RDBMSs,
>> and analyzing the data with extensive Apache Hadoop MapReduce support.
>>
>> Now it support MySQL in gora-sql model.
>>
>>  http://gora.apache.org/
>>
>>
>> On Tue, Aug 21, 2012 at 5:39 PM, Harsh J <harsh@cloudera.com> wrote:
>>
>>> Tharindu,
>>>
>>> (Am assuming you've done enough research to know that there's benefit
>>> in what you're attempting to do.)
>>>
>>> Locality of tasks are determined by the job's InputFormat class.
>>> Specifically, the locality information returned by the InputSplit
>>> objects via InputFormat#getSplits(…) API is what the MR scheduler
>>> looks at when trying to launch data local tasks.
>>>
>>> You can tweak your InputFormat (the one that uses this DB as input?)
>>> to return relevant locations based on your "DB Cluster", in order to
>>> achieve this.
>>>
>>> On Tue, Aug 21, 2012 at 2:36 PM, Tharindu Mathew <mccloud35@gmail.com>
>>> wrote:
>>> > Hi,
>>> >
>>> > I'm doing some research that involves pulling data stored in a mysql
>>> cluster
>>> > directly for a map reduce job, without storing the data in HDFS.
>>> >
>>> > I'd like to run hadoop task tracker nodes directly on the mysql cluster
>>> > nodes. The purpose of this being, starting mappers directly in the node
>>> > closest to the data if possible (data locality).
>>> >
>>> > I notice that with HDFS, since the name node knows exactly where each
>>> data
>>> > block is, it uses this to achieve data locality.
>>> >
>>> > Is there a way to achieve my requirement possibly by extending the
>>> name node
>>> > or otherwise?
>>> >
>>> > Thanks in advance.
>>> >
>>> > --
>>> > Regards,
>>> >
>>> > Tharindu
>>> >
>>> > blog: http://mackiemathew.com/
>>> >
>>>
>>>
>>>
>>> --
>>> Harsh J
>>>
>>
>>
>>
>> --
>> Don't Grow Old, Grow Up... :-)
>>
>
>
>
> --
> Regards,
>
> Tharindu
>
> blog: http://mackiemathew.com/
>
>
>


-- 
Regards,

Tharindu

blog: http://mackiemathew.com/

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