Quang-Nhat HOANG-XUAN created PIG-4066:
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Summary: An optimization for ROLLUP operation in Pig
Key: PIG-4066
URL: https://issues.apache.org/jira/browse/PIG-4066
Project: Pig
Issue Type: Improvement
Reporter: Quang-Nhat HOANG-XUAN
This patch aims at addressing the current limitation of the ROLLUP operator in
PIG: most of the work is done in the Map phase of the underlying MapReduce job
to generate all possible intermediate keys that the reducer use to aggregate
and produce the ROLLUP output. Based on our previous work: “On the design space
of MapReduce ROLLUP aggregates”
(http://www.eurecom.fr/en/publication/4212/download/rs-publi-4212_2.pdf), we
show that the design space for a ROLLUP implementation allows for a different
approach (in-reducer grouping, IRG), in which less work is done in the Map
phase and the grouping is done in the Reduce phase. This patch presents the
most efficient implementation we designed (Hybrid IRG), which allows defining a
parameter to balance between parallelism (in the reducers) and communication
cost.
This patch contains the following features:
1. The new ROLLUP approach: IRG, Hybrid IRG.
2. The PIVOT clause in CUBE operators.
3. Test cases.
The new syntax to use our ROLLUP approach:
alias = CUBE rel BY
{ CUBE col_ref | ROLLUP col_ref [PIVOT pivot_value]} [, { CUBE col_ref | ROLLUP
col_ref [PIVOT pivot_value]}
...]
In case there is multiple ROLLUP operator in one CUBE clause, the last ROLLUP
operator will be executed with our approach (IRG, Hybrid IRG) while the
remaining ROLLUP ahead will be executed with the default approach.
We have already made some experiments for comparison between our ROLLUP
implementation and the current ROLLUP. More information can be found at here:
http://hxquangnhat.github.io/PIG-ROLLUP-H2IRG/
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