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https://issues.apache.org/jira/browse/HADOOP-17596?focusedWorklogId=595922&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-595922
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ASF GitHub Bot logged work on HADOOP-17596:
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Author: ASF GitHub Bot
Created on: 13/May/21 06:55
Start Date: 13/May/21 06:55
Worklog Time Spent: 10m
Work Description: anoopsjohn commented on pull request #2795:
URL: https://github.com/apache/hadoop/pull/2795#issuecomment-840357499
When there are not many parallel FIS reads, this (possible) reduction in
read ahead parallelism will affect the read throughput? Specially Spark kind
of? From HBase standpoint this is acceptable.
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Issue Time Tracking
-------------------
Worklog Id: (was: 595922)
Time Spent: 1h 10m (was: 1h)
> ABFS: Change default Readahead Queue Depth from num(processors) to const
> ------------------------------------------------------------------------
>
> Key: HADOOP-17596
> URL: https://issues.apache.org/jira/browse/HADOOP-17596
> Project: Hadoop Common
> Issue Type: Sub-task
> Components: fs/azure
> Affects Versions: 3.3.1
> Reporter: Sumangala Patki
> Assignee: Sumangala Patki
> Priority: Major
> Labels: pull-request-available
> Time Spent: 1h 10m
> Remaining Estimate: 0h
>
> The default value of readahead queue depth is currently set to the number of
> available processors. However, this can result in one inputstream instance
> consuming more processor time. To ensure equal thread allocation during read
> for all inputstreams created in a session, we change the default readahead
> queue depth to a constant (2).
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