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Re: HBase and Datawarehouse
Multiple RS per host?

That seems very counter intuitive and potentially problematic w M/R jobs.
Could you expand on this?



On Apr 30, 2013, at 12:38 PM, 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,