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https://issues.apache.org/jira/browse/TEZ-2104?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14321182#comment-14321182
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Gopal V edited comment on TEZ-2104 at 2/14/15 2:47 AM:
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The cross-product edge has special affinity scheduling optimizations for one of
the edges (the one which moves the most amount of data) to avoid re-merging the
input streams during node/container co-located runs.
The built-in edge opens up a need for evolving affinity optimizations related
to temporal locality in the scheduler.
was (Author: gopalv):
The cross-product edge has special affinity scheduling optimizations for one of
the edges (the one which moves the most amount of data) to avoid re-merging the
input streams during node/container co-located runs.
The built-in edge opens up a need to evolving affinity optimizations related to
temporal locality in the scheduler.
> A CrossProductEdge which produces synthetic cross-product parallelism
> ---------------------------------------------------------------------
>
> Key: TEZ-2104
> URL: https://issues.apache.org/jira/browse/TEZ-2104
> Project: Apache Tez
> Issue Type: New Feature
> Reporter: Gopal V
> Labels: gsoc, gsoc2015, hadoop, hive, java, tez
>
> Instead of producing duplicate data for the synthetic cross-product, to fit
> into partitions, the amount of net IO can be vastly reduced by a special
> purpose cross-product data movement edge.
> The Shuffle edge routes each partition's output to a single reducer, while
> the cross-product edge routes it into a matrix of reducers without actually
> duplicating the disk data.
> A partitioning scheme with 3 partitions on the lhs and rhs of a join
> operation can be routed into 9 reducers by performing a cross-product similar
> to
> (1,2,3) x (a,b,c) = [(1,a), (1,b), (1,c), (2,a), (2,b) ...]
> This turns a single task cross-product model into a distributed cross product.
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