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https://issues.apache.org/jira/browse/MAPREDUCE-1114?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12786225#action_12786225
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Doug Cutting commented on MAPREDUCE-1114:
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> I look at this as a 60% speedup in my development cycle rather than a few %
> speedup in the full build.
I agree with this logic. My most common development cycle is to run a single
unit test. For Avro this takes just a few seconds, and I'm willing to wait
without finding a new task to work on. With Hadoop this takes long enough that
I switch to doing something else, lose my context, etc. Improving this
significantly will significantly improve many developers productivity.
I wonder if we can simply check if build/ivy/lib/Hadoop-Hdfs/{common,test}
exist, and, if they do, assumes they're up-to-date, and only runs Ivy
otherwise. Might that be simpler?
> Speed up ivy resolution in builds with clever caching
> -----------------------------------------------------
>
> Key: MAPREDUCE-1114
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-1114
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: build
> Affects Versions: 0.22.0
> Reporter: Todd Lipcon
> Assignee: Todd Lipcon
> Priority: Minor
> Attachments: mapreduce-1114.txt, mapreduce-1114.txt,
> mapreduce-1114.txt
>
>
> An awful lot of time is spent in the ivy:resolve parts of the build, even
> when all of the dependencies have been fetched and cached. Profiling showed
> this was in XML parsing. I have a sort-of-ugly hack which speeds up
> incremental compiles (and more importantly "ant test") significantly using
> some ant macros to cache the resolved classpaths.
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