First, I have not tried it myself. However, what I have heard it has some
basic SQL features so you can query you HBase table like query content on
HDFS using Hive.
So it is not "query a simple column", I believe you can do joins and other
SQL queries. Maybe you can wrap up an EMR cluster with Hbase preconfigured
and give it a try.

Sorry cannot provide more detailed explanation and help.



On Tue, Apr 8, 2014 at 10:17 AM, Flavio Pompermaier <pomperma...@okkam.it>wrote:

> Thanks for the quick reply Bin. Phenix is something I'm going to try for
> sure but is seems somehow useless if I can use Spark.
> Probably, as you said, since Phoenix use a dedicated data structure within
> each HBase Table has a more effective memory usage but if I need to
> deserialize data stored in a HBase cell I still have to read in memory that
> object and thus I need Spark. From what I understood Phoenix is good if I
> have to query a simple column of HBase but things get really complicated if
> I have to add an index for each column in my table and I store complex
> object within the cells. Is it correct?
>
> Best,
> Flavio
>
>
>
>
> On Tue, Apr 8, 2014 at 6:05 PM, Bin Wang <binwang...@gmail.com> wrote:
>
>> Hi Flavio,
>>
>> I happened to attend, actually attending the 2014 Apache Conf, I heard a
>> project called "Apache Phoenix", which fully leverage HBase and suppose to
>> be 1000x faster than Hive. And it is not memory bounded, in which case sets
>> up a limit for Spark. It is still in the incubating group and the "stats"
>> functions spark has already implemented are still on the roadmap. I am not
>> sure whether it will be good but might be something interesting to check
>> out.
>>
>> /usr/bin
>>
>>
>> On Tue, Apr 8, 2014 at 9:57 AM, Flavio Pompermaier 
>> <pomperma...@okkam.it>wrote:
>>
>>> Hi to everybody,
>>>
>>>  in these days I looked a bit at the recent evolution of the big data
>>> stacks and it seems that HBase is somehow fading away in favour of
>>> Spark+HDFS. Am I correct?
>>> Do you think that Spark and HBase should work together or not?
>>>
>>> Best regards,
>>> Flavio
>>>
>>

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