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From Mayur Rustagi <mayur.rust...@gmail.com>
Subject Re: SQL on Spark - Shark or SparkSQL
Date Sun, 30 Mar 2014 23:46:08 GMT
+1 Have done a few installations of Shark with customers using Hive, they
love it. Would be good to maintain compatibility with Metastore & QL till
we have substantial reason to break off (like BlinkDB).

Mayur Rustagi
Ph: +1 (760) 203 3257
http://www.sigmoidanalytics.com
@mayur_rustagi <https://twitter.com/mayur_rustagi>



On Sun, Mar 30, 2014 at 2:46 AM, Nicholas Chammas <
nicholas.chammas@gmail.com> wrote:

> This is a great question. We are in the same position, having not invested
> in Hive yet and looking at various options for SQL-on-Hadoop.
>
>
> On Sat, Mar 29, 2014 at 9:48 PM, Manoj Samel <manojsameltech@gmail.com>wrote:
>
>> Hi,
>>
>> In context of the recent Spark SQL announcement (
>> http://databricks.com/blog/2014/03/26/Spark-SQL-manipulating-structured-data-using-Spark.html
>> ).
>>
>> If there is no existing investment in Hive/Shark, would it be worth
>> starting a new SQL work using SparkSQL rather than Shark ?
>>
>> * It seems Shark SQL core will use more and more of SparkSQL
>> * From the blog, it seems Shark has baggage from Hive, that is not needed
>> in this case
>>
>> On the other hand, there seems to be two shortcomings of SparkSQL (from a
>> quick scan of blog and doc)
>>
>> * SparkSQL will have less features than Shark/Hive QL, at least for now.
>> * The standalone SharkServer feature will not be available in SparkSQL.
>>
>> Can someone from Databricks shed light on what is the long term roadmap?
>> It will help in avoiding investing in older/two technologies for work with
>> no Hive needs.
>>
>> Thanks,
>>
>> PS: Great work on SparkSQL
>>
>>
>

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