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https://issues.apache.org/jira/browse/KYLIN-3925?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16808587#comment-16808587
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ASF GitHub Bot commented on KYLIN-3925:
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kyotoYaho commented on pull request #580: KYLIN-3925 Add reduce step for
FilterRecommendCuboidDataJob & UpdateO…
URL: https://github.com/apache/kylin/pull/580
…ldCuboidShardJob to avoid generating small hdfs files
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> Add reduce step for FilterRecommendCuboidDataJob & UpdateOldCuboidShardJob to
> avoid generating small hdfs files
> ---------------------------------------------------------------------------------------------------------------
>
> Key: KYLIN-3925
> URL: https://issues.apache.org/jira/browse/KYLIN-3925
> Project: Kylin
> Issue Type: Improvement
> Reporter: Zhong Yanghong
> Assignee: Zhong Yanghong
> Priority: Major
>
> Previously when doing cube optimization, there're two map only MR jobs:
> *FilterRecommendCuboidDataJob* & *UpdateOldCuboidShardJob*. The benefit of
> map only job is to avoid shuffling. However, this benefit will bring a more
> severe issue, too many small hdfs files.
> Suppose there're 10 hdfs files for current cuboids data and each with 500M.
> If the block size is 100M, there'll be 10*(500/100) mappers for the map only
> job *FilterRecommendCuboidDataJob*. Each mapper will generate a hdfs file.
> Finally there'll be 50 hdfs files. Since the job
> *FilterRecommendCuboidDataJob* will filter out the cuboid data used for
> future, the data size of each file will be less than 100M. In some cases, it
> will be even less than 50M.
> To avoid this kind of small hdfs file issue, it's better to add a reduce step
> to control the final output hdfs file number.
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