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https://issues.apache.org/jira/browse/CRUNCH-284?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13800682#comment-13800682
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Chao Shi commented on CRUNCH-284:
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Another use case is (which I came into a few months ago):
PCollection in = pipeline.read(...)
PCollection tmp = someExpensiveFn(in)
PCollection part1 = f1(tmp)
PCollection part2 = f2(tmp)
pipelien.write(part1.groupByKey...)
pipeline.write(part2.groupByKey...)
I hope we can find an approach to tell crunch that someExpensiveFn is really
expensive and should be executed only once.
> Optimize for minimal disk i/o rather than the number of stages?
> ---------------------------------------------------------------
>
> Key: CRUNCH-284
> URL: https://issues.apache.org/jira/browse/CRUNCH-284
> Project: Crunch
> Issue Type: Bug
> Reporter: Chao Shi
>
> I have a pipeline as follows:
> PCollection in = pipeline.read(...)
> PCollection part1 = f1(in)
> PCollection part2 = f2(in)
> pipelien.write(part1.groupByKey...)
> pipeline.write(part2.groupByKey...)
> where f1 extracts a small potion from "in" and f2 returns the rest. Crunch
> optimizes the pipeline into two independent MR jobs, both of which fully read
> the input.
> I think the ideal MRs should be a map-only job reads the input and split them
> to two outputs, and then two MRs read them respectively.
> The problem is that Crunch minimizes the number of MR stages, which is
> optimal for most cases, but not optimal in this case.
> What do you think of this folks?
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