Please find the data requirements for our use case below :

Raw data processing
----------------------------------
1. Data is populated into hdfs , after etl around 3 billion puts per day in
to hbase

2. Oldest data after X days to be deleted from hbase

Aggregates processing
----------------------------------
3 billion reads per day ... Large scan or reads

KV size around 1 KB Daily Processing, raw and aggregates, via M/R jobs Hive
queries in future, but not of immediate focus
On Feb 5, 2014 12:48 AM, "Vladimir Rodionov" <[email protected]>
wrote:

> Yes,
>
> 1. What is the expected avg and peak load in writes/updates/deletes/reads?
> 2. What is the average size of a KV?
> 3. Reads/small scans/medium/large scan %%
> 4. Do you plan M/R jobs, Hive query?
>
>
> Best regards,
> Vladimir Rodionov
> Principal Platform Engineer
> Carrier IQ, www.carrieriq.com
> e-mail: [email protected]
>
> ________________________________________
> From: Nick Xie [[email protected]]
> Sent: Tuesday, February 04, 2014 10:02 AM
> To: [email protected]
> Subject: Re: Regarding Hardware configuration for HBase cluster
>
> I guess you'd better describe a little bit more about your applications.
> Does the data increase over the time at all?
>
> Nick
>
>
> On Tue, Feb 4, 2014 at 5:22 AM, suresh babu <[email protected]> wrote:
>
> > Hi folks,
> >
> > We are trying to setup HBase cluster for the following requirement:
> >
> > We have to maintain data of size around 800TB,
> >
> > For the above requirement,please suggest me the best hardware
> configuration
> > details like
> >
> > 1)how many disks to consider for machine and the  capacity of disks ,for
> > example, 16/24 disks per node with 1/2TB capacity per each disk
> >
> > 2) which compression method is suited for production environment , space
> is
> > not a major limitation , but speed is of prime concern for my use case
> >
> > 3) how many CPU Cores should be configured for each node/machine ?  Or
> > ideal ratio of number of cores to the number of disks,for example
> > 1core/1disk ?
> >
> > Regards,
> > Kaushik
> >
>
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