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From "Steve Loughran (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HADOOP-11794) distcp can copy blocks in parallel
Date Fri, 17 Mar 2017 11:25:41 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-11794?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15929782#comment-15929782
] 

Steve Loughran commented on HADOOP-11794:
-----------------------------------------

# this is an opportunity to switch distcp over to using the slf4j logger class; existing logging
can be left alone, but all new logs can switch to the inline logging
# What does "YJD ls before distcp" in tests mean?
# {{TestDistCpSystem}} does a cleanup in {{testDistcpLargeFile}} as the last operation in
a successful test run. Does it still cleanup on a failure? If not, what is the final state
of the call & does it matter
# in the s3a tests we now have a -Pscale profile for scalable tests, and can set file sizes.
It might be nice to have here, but it's a complex piece of work: not really justifiable except
as a bigger set of scale tests


> distcp can copy blocks in parallel
> ----------------------------------
>
>                 Key: HADOOP-11794
>                 URL: https://issues.apache.org/jira/browse/HADOOP-11794
>             Project: Hadoop Common
>          Issue Type: Improvement
>          Components: tools/distcp
>    Affects Versions: 0.21.0
>            Reporter: dhruba borthakur
>            Assignee: Yongjun Zhang
>         Attachments: HADOOP-11794.001.patch, HADOOP-11794.002.patch, HADOOP-11794.003.patch,
HADOOP-11794.004.patch, HADOOP-11794.005.patch, HADOOP-11794.006.patch, HADOOP-11794.007.patch,
HADOOP-11794.008.patch, MAPREDUCE-2257.patch
>
>
> The minimum unit of work for a distcp task is a file. We have files that are greater
than 1 TB with a block size of  1 GB. If we use distcp to copy these files, the tasks either
take a long long long time or finally fails. A better way for distcp would be to copy all
the source blocks in parallel, and then stich the blocks back to files at the destination
via the HDFS Concat API (HDFS-222)



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