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https://issues.apache.org/jira/browse/PIG-483?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13017479#comment-13017479
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Zubair Nabi commented on PIG-483:
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But how can one make the call that the data is small enough to apply a single
reduce 'order-by'. As I understand, the distribution helps in proper
load-balancing in case of skewed datasets. The first MapReduce pass or sampling
is used to built a partitioner and in the second pass, that partitioner is used
in conjunction with the order-by key as the grouping key. This ensures that
every reduce gets a fair workload. So, without any a-priori knowledge, how can
we determine whether we need a two-stage order-by or a single stage order-by
with a single reduce?
> PERFORMANCE: different strategies for large and small order bys
> ---------------------------------------------------------------
>
> Key: PIG-483
> URL: https://issues.apache.org/jira/browse/PIG-483
> Project: Pig
> Issue Type: Improvement
> Affects Versions: 0.2.0
> Reporter: Olga Natkovich
> Labels: gsoc2011
>
> Currently pig always does a multi-pass order by where it first determines a
> distribution for the keys and then orders in a second pass. This avoids the
> necessity of having a single reducer. However, in cases where the data is
> small enough to fit into a single reducer, this is inefficient. For small
> data sets it would be good to realize the small size of the set and do the
> order by in a single pass with a single reducer.
> This is a candidate project for Google summer of code 2011. More information
> about the program can be found at http://wiki.apache.org/pig/GSoc2011
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