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From "Hiller, Dean" <Dean.Hil...@nrel.gov>
Subject Re: 1000's of column families
Date Tue, 02 Oct 2012 13:28:01 GMT
Thanks for the idea but…(but please keep thinking on it)...

100% what we don't want since partitioned data resides on the same node.
I want to map/reduce the column families and leverage the parallel disks

:( :(

I am sure others would want to do the same…..We almost need a feature of
virtual Column Families and column family should really not be column
family but should be called ReplicationGroup or something where
replication is configured for all CF's in that group.

ANYONE have any other ideas???

Dean

On 10/2/12 7:20 AM, "Brian O'Neill" <boneill42@gmail.com> wrote:

>
>Without putting too much thought into it...
>
>Given the underlying architecture, I think you could/would have to write
>your own partitioner, which would partition based on the prefix/virtual
>keyspace.  
>
>-brian
>
>---
>Brian O'Neill
>Lead Architect, Software Development
> 
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>On 10/2/12 9:00 AM, "Ben Hood" <0x6e6562@gmail.com> wrote:
>
>>Dean,
>>
>>On Tue, Oct 2, 2012 at 1:37 PM, Hiller, Dean <Dean.Hiller@nrel.gov>
>>wrote:
>>> Ben,
>>>   to address your question, read my last post but to summarize, yes,
>>>there
>>> is less overhead in memory to prefix keys than manage multiple Cfs
>>>EXCEPT
>>> when doing map/reduce.  Doing map/reduce, you will now have HUGE
>>>overhead
>>> in reading a whole slew of rows you don't care about as you can't
>>> map/reduce a single virtual CF but must map/reduce the whole CF wasting
>>> TONS of resources.
>>
>>That's a good point that I hadn't considered beforehand, especially as
>>I'd like to run MR jobs against these CFs.
>>
>>Is this limitation inherent in the way that Cassandra is modelled as
>>input for Hadoop or could you write a custom slice query to only feed
>>in one particular prefix into Hadoop?
>>
>>Cheers,
>>
>>Ben
>
>

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