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https://issues.apache.org/jira/browse/PIG-2167?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Daniel Dai updated PIG-2167:
----------------------------

    Description: 
Computing aggregates over a cube of several dimensions is a common operation in 
data warehousing.

The standard SQL syntax is "GROUP relation BY dim1, dim2, dim3 WITH CUBE" -- 
which in addition to all dim1-2-3, produces aggregations for just dim1, just 
dim1 and dim2, etc. NULL is generally used to represent "all".

A presentation by Arnab Nandi describes how one might implement efficient 
cubing in Map-Reduce here: http://pdf.cx/44wrk

We can start with the naive solution which only works for algebraic measures, 
and work up from there.

This is a candidate project for Google summer of code 2012. More information 
about the program can be found at 
https://cwiki.apache.org/confluence/display/PIG/GSoc2012

  was:
Computing aggregates over a cube of several dimensions is a common operation in 
data warehousing.

The standard SQL syntax is "GROUP relation BY dim1, dim2, dim3 WITH CUBE" -- 
which in addition to all dim1-2-3, produces aggregations for just dim1, just 
dim1 and dim2, etc. NULL is generally used to represent "all".

A presentation by Arnab Nandi describes how one might implement efficient 
cubing in Map-Reduce here: http://pdf.cx/44wrk

We can start with the naive solution which only works for algebraic measures, 
and work up from there.

    
> CUBE operation in Pig
> ---------------------
>
>                 Key: PIG-2167
>                 URL: https://issues.apache.org/jira/browse/PIG-2167
>             Project: Pig
>          Issue Type: New Feature
>            Reporter: Dmitriy V. Ryaboy
>              Labels: gsoc2012
>
> Computing aggregates over a cube of several dimensions is a common operation 
> in data warehousing.
> The standard SQL syntax is "GROUP relation BY dim1, dim2, dim3 WITH CUBE" -- 
> which in addition to all dim1-2-3, produces aggregations for just dim1, just 
> dim1 and dim2, etc. NULL is generally used to represent "all".
> A presentation by Arnab Nandi describes how one might implement efficient 
> cubing in Map-Reduce here: http://pdf.cx/44wrk
> We can start with the naive solution which only works for algebraic measures, 
> and work up from there.
> This is a candidate project for Google summer of code 2012. More information 
> about the program can be found at 
> https://cwiki.apache.org/confluence/display/PIG/GSoc2012

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