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https://issues.apache.org/jira/browse/HADOOP-17250?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sneha Vijayarajan updated HADOOP-17250:
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Description:
Random read if marginally read ahead was seen to improve perf for a TPCH query.
was:
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
and resulted in higher job runtime.
When these jobs were run against Gen1 which always reads in buffer size , the
jobs fared well.
In this Jira we try to provide a control over config on random read to be of
requested size or buffer size.
> ABFS: Random read perf improvement
> ----------------------------------
>
> Key: HADOOP-17250
> URL: https://issues.apache.org/jira/browse/HADOOP-17250
> 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, pull-request-available
> Time Spent: 2h
> Remaining Estimate: 0h
>
> Random read if marginally read ahead was seen to improve perf for a TPCH
> query.
>
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