[
https://issues.apache.org/jira/browse/HADOOP-17296?focusedWorklogId=517372&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-517372
]
ASF GitHub Bot logged work on HADOOP-17296:
-------------------------------------------
Author: ASF GitHub Bot
Created on: 27/Nov/20 14:24
Start Date: 27/Nov/20 14:24
Worklog Time Spent: 10m
Work Description: steveloughran commented on pull request #2368:
URL: https://github.com/apache/hadoop/pull/2368#issuecomment-734859096
ok, merged into trunk. For 3.3.x can you do the backport, retest and put up
a new PR for me to merge in there? That branch doesn't have guava under the
thirdparty packaging, so a safe cherrypick isn't enough to prove it will
compile/run. Don't worry about reordering the import references, just edit out
the o.a.h.thirdparty prefixes and leave as is.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
Issue Time Tracking
-------------------
Worklog Id: (was: 517372)
Remaining Estimate: 0h
Time Spent: 10m
> ABFS: Allow Random Reads to be of Buffer Size
> ---------------------------------------------
>
> Key: HADOOP-17296
> URL: https://issues.apache.org/jira/browse/HADOOP-17296
> Project: Hadoop Common
> Issue Type: Sub-task
> Components: fs/azure
> Affects Versions: 3.3.0
> Reporter: Sneha Vijayarajan
> Assignee: Sneha Vijayarajan
> Priority: Major
> Labels: abfsactive
> Time Spent: 10m
> Remaining Estimate: 0h
>
> ADLS Gen2/ABFS driver is optimized to read only the bytes that are requested
> for when the read pattern is random.
> It was observed in some spark jobs that though the reads are random, the next
> read doesn't skip by a lot and can be served by the earlier read if read was
> done in buffer size. As a result the job triggered a higher count of read
> calls/higher IOPS, resulting in higher IOPS throttling and hence resulted in
> higher job runtime.
> When these jobs were run against Gen1 which always reads in buffer size , the
> jobs fared well.
> This Jira attempts to get a Gen1 customer migrating to Gen2 get the same
> overall i/o pattern as gen1 and the same perf characteristics.
> *+Stats from Customer Job:+*
>
> |*Customer Job*|*Gen 1 timing*|*Gen 2 Without patch*|*Gen2 with patch and
> RAH=0*|
> |Job1|2 h 47 m|3 h 45 m|2 h 27 mins|
> |Job2|2 h 17 m|3 h 24 m|2 h 39 mins|
> |Job3|3 h 16 m|4 h 29 m|3 h 21 mins|
> |Job4|1 h 59 m|3 h 12 m|2 h 28 mins|
>
> *+Stats from Internal TPCDs runs+*
> [Total number of TPCDs queries per suite run = 80
> Full suite repeat run count per config = 3]
> | |*Gen1*|Gen2 Without patch|*Gen2 With patch and RAH=0*
> *(Gen2 in Gen1 config)*|*Gen2 With patch and RAH=2*|
> |%Run Duration|100|140|213|70-90|
> |%Read IOPS|100|106|98|110-115|
>
> *Without patch = default Jar with random read logic
> *With patch=Modified Jar with change to always read buffer size
> *RAH=ReadAheadQueueDepth
>
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
