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From "renga.kannan" <renga.kan...@gmail.com>
Subject Is SPARK is the right choice for traditional OLAP query processing?
Date Tue, 21 Jul 2015 00:04:56 GMT
All,
I really appreciate anyone's input on this. We are having a very simple
traditional OLAP query processing use case. Our use case is as follows.


1. We have a customer sales order table data coming from RDBMs table. 
2. There are many dimension columns in the sales order table. For each of
those dimensions, we have individual dimension tables that stores the
dimension record sets.
3. We also have some BI like hierarchies that is defined for dimension data
set.

What we want for business users is as follows.?

1. We wanted to show some aggregated values from sales Order transaction
table columns.
2. User would like to filter these with specific dimension values from
dimension table.
3. User should be able to drill down from higher level to lower level by
traversing hierarchy on dimension


We want these use actions respond within 2 to 5 seconds.


We are thinking about using SPARK as our backend enginee to sever data to
these front end application.


Has anyone tried using SPARK for these kind of use cases. These are all
traditional use cases in BI space. If so, can SPARK respond to these queries
with in 2 to 5 seconds for large data sets.

Thanks,
Renga



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