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Re: HBase and Datawarehouse
Multiple RS' per host gets you around the WAL bottleneck as well. But
it's operationally less than ideal. Do you usually recommend this
approach, Andy? I've shied away from it mostly.

On Apr 30, 2013, at 10:38 AM, Andrew Purtell <[EMAIL PROTECTED]> wrote:

> Rules of thumb for starting off safely and for easing support issues are
> really good to have, but there are no hard barriers or singular approaches:
> use Java 7 + G1GC, disable HBase blockcache in lieu of OS blockcache, run
> multiple regionservers per host. It is going to depend on how the cluster
> is used and loaded. If we are talking about coprocessors, then effective
> limits are less clear, using a coprocessor to integrate an external process
> implemented with native code communicating over memory mapped files in
> /dev/shm isn't outside what is possible (strawman alert).
> On Tue, Apr 30, 2013 at 5:01 AM, Kevin O'dell <[EMAIL PROTECTED]>wrote:
>> Asaf,
>>  The heap barrier is something of a legend :)  You can ask 10 different
>> HBase committers what they think the max heap is and get 10 different
>> answers.  This is my take on heap sizes from the many clusters I have dealt
>> with:
>> 8GB -> Standard heap size, and tends to run fine without any tuning
>> 12GB -> Needs some TLC with regards to JVM tuning if your workload tends
>> cause churn(usually blockcache)
>> 16GB -> GC tuning is a must, and now we need to start looking into MSLab
>> and ZK timeouts
>> 20GB -> Same as 16GB in regards to tuning, but we tend to need to raise the
>> ZK timeout a little higher
>> 32GB -> We do have a couple people running this high, but the pain out
>> weighs the gains(IMHO)
>> 64GB -> Let me know how it goes :)
>> On Tue, Apr 30, 2013 at 4:07 AM, Andrew Purtell <[EMAIL PROTECTED]>
>> wrote:
>>> I don't wish to be rude, but you are making odd claims as fact as
>>> "mentioned in a couple of posts". It will be difficult to have a serious
>>> conversation. I encourage you to test your hypotheses and let us know if
>> in
>>> fact there is a JVM "heap barrier" (and where it may be).
>>> On Monday, April 29, 2013, Asaf Mesika wrote:
>>>> I think for Pheoenix truly to succeed, it's need HBase to break the JVM
>>>> Heap barrier of 12G as I saw mentioned in couple of posts. since Lots
>> of
>>>> analytics queries utilize memory, thus since its memory is shared with
>>>> HBase, there's so much you can do on 12GB heap. On the other hand, if
>>>> Pheonix was implemented outside HBase on the same machine (like Drill
>> or
>>>> Impala is doing), you can have 60GB for this process, running many OLAP
>>>> queries in parallel, utilizing the same data set.
>>>> On Mon, Apr 29, 2013 at 9:08 PM, Andrew Purtell <[EMAIL PROTECTED]
>>> <javascript:;>>
>>>> wrote:
>>>>>> HBase is not really intended for heavy data crunching
>>>>> Yes it is. This is why we have first class MapReduce integration and
>>>>> optimized scanners.
>>>>> Recent versions, like 0.94, also do pretty well with the 'O' part of
>>>> OLAP.
>>>>> Urban Airship's Datacube is an example of a successful OLAP project
>>>>> implemented on HBase: http://github.com/urbanairship/datacube
>>>>> "Urban Airship uses the datacube project to support its analytics
>> stack
>>>> for
>>>>> mobile apps. We handle about ~10K events per second per node."
>>>>> Also there is Adobe's SaasBase:
>>>>> http://www.slideshare.net/clehene/hbase-and-hadoop-at-adobe
>>>>> Etc.
>>>>> Where an HBase OLAP application will differ tremendously from a
>>>> traditional
>>>>> data warehouse is of course in the interface to the datastore. You
>> have
>>>> to
>>>>> design and speak in the language of the HBase API, though Phoenix (
>>>>> https://github.com/forcedotcom/phoenix) is changing that.
>>>>> On Sun, Apr 28, 2013 at 10:21 PM, anil gupta <[EMAIL PROTECTED]
>>> <javascript:;>
>>>>> wrote:
>>>>>> Hi Kiran,