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Posted to common-issues@hadoop.apache.org by "Steve Loughran (JIRA)" <ji...@apache.org> on 2017/08/12 17:28:00 UTC
[jira] [Commented] (HADOOP-14766) Add an object store high
performance dfs put command
[ https://issues.apache.org/jira/browse/HADOOP-14766?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16124648#comment-16124648 ]
Steve Loughran commented on HADOOP-14766:
-----------------------------------------
+if you are trying to reduce risk of throttling, you may even want to look at filesize before choosing which to upload, & try to mix big files with little ones. You'd want to sort them & start the largest few off first to stop it being a bottleneck, then go for the rest.
without store throttling and bandwidth limitations, the optimal scheduling would seem to be just queue the largest files for upload first & let them sort themselves out, finishing off with all the small files after. But: those small files take up lots of HTTP requests (3x HEAD & 1 PUT & 1 DELETE with depth(file) entries), & with SSE-KMS, one createKey call. Mixing them in with the larger uploads, as well as mixing paths, would appear to be less prone to throttling
> Add an object store high performance dfs put command
> ----------------------------------------------------
>
> Key: HADOOP-14766
> URL: https://issues.apache.org/jira/browse/HADOOP-14766
> Project: Hadoop Common
> Issue Type: Sub-task
> Components: fs, fs/s3
> Affects Versions: 2.8.1
> Reporter: Steve Loughran
>
> {{hdfs put local s3a://path}} is suboptimal as it treewalks down down the source tree then, sequentially, copies up the file through copying the file (opened as a stream) contents to a buffer, writes that to the dest file, repeats.
> For S3A that hurts because
> * it;s doing the upload inefficiently: the file can be uploaded just by handling the pathname to the AWS xter manager
> * it is doing it sequentially, when some parallelised upload would work.
> * as the ordering of the files to upload is a recursive treewalk, it doesn't spread the upload across multiple shards.
> Better:
> * build the list of files to upload
> * upload in parallel, picking entries from the list at random and spreading across a pool of uploaders
> * upload straight from local file (copyFromLocalFile()
> * track IO load (files created/second) to estimate risk of throttling.
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