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From James Taylor <jtay...@salesforce.com>
Subject Re: HBase and Datawarehouse
Date Tue, 30 Apr 2013 06:28:14 GMT
Phoenix will succeed if HBase succeeds. Phoenix just makes it easier to 
drive HBase to it's maximum capability. IMHO, if HBase is to make 
further gains in the OLAP space, scans need to be faster and new, more 
compressed columnar-store type block formats need to be developed.

Running inside HBase is what gives Phoenix most of its performance 
advantage. Have you seen our numbers against Impala: 
https://github.com/forcedotcom/phoenix/wiki/Performance? Drill will need 
something to efficiently execute a query plan against HBase and Phoenix 
is a good fit here.



On 04/29/2013 10:54 PM, 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 <apurtell@apache.org> 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 <anilgupta84@gmail.com>
>> wrote:
>>> Hi Kiran,
>>> In HBase the data is denormalized but at the core HBase is KeyValue based
>>> database meant for lookups or queries that expect response in
>> milliseconds.
>>> OLAP i.e. data warehouse usually involves heavy data crunching. HBase is
>>> not really intended for heavy data crunching. If you want to just store
>>> denoramlized data and do simple queries then HBase is good. For OLAP kind
>>> of stuff, you can make HBase work but IMO you will be better off using
>> Hive
>>> for  data warehousing.
>>> HTH,
>>> Anil Gupta
>>> On Sun, Apr 28, 2013 at 8:39 PM, Kiran <kiranvk2011@gmail.com> wrote:
>>>> But in HBase data can be said to be in  denormalised state as the
>>>> methodology
>>>> used for storage is a (column family:column) based flexible schema
>> .Also,
>>>> from Google's  big table paper it is evident that HBase is capable of
>>> doing
>>>> OLAP.SO where does the difference lie?
>>>> --
>>>> View this message in context:
>> http://apache-hbase.679495.n3.nabble.com/HBase-and-Datawarehouse-tp4043172p4043216.html
>>>> Sent from the HBase User mailing list archive at Nabble.com.
>> --
>> Best regards,
>>     - Andy
>> Problems worthy of attack prove their worth by hitting back. - Piet Hein
>> (via Tom White)

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