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https://issues.apache.org/jira/browse/SPARK-24013?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16448093#comment-16448093
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Juliusz Sompolski edited comment on SPARK-24013 at 4/23/18 1:11 PM:
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Hi [~mgaido]
I tested again on current master (afbdf427302aba858f95205ecef7667f412b2a6a) and
I reproduce it:
!screenshot-1.png!
Maybe you need to bump up 10000000 to something higher when running on a bigger
cluster that splits the range into more tasks?
For me it grinds to a halt after about 2500000 per task.
was (Author: juliuszsompolski):
Hi [~mgaido]
I tested again on current master (afbdf427302aba858f95205ecef7667f412b2a6a) and
I reproduce it:
!screenshot-1.png!
Maybe you need to bump up 1000000 to something higher when running on a bigger
cluster that splits the range into more tasks?
For me it grinds to a halt after about 2500000 per task.
> ApproximatePercentile grinds to a halt on sorted input.
> -------------------------------------------------------
>
> Key: SPARK-24013
> URL: https://issues.apache.org/jira/browse/SPARK-24013
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.3.0
> Reporter: Juliusz Sompolski
> Priority: Major
> Attachments: screenshot-1.png
>
>
> Running
> {code}
> sql("select approx_percentile(rid, array(0.1)) from (select rand() as rid
> from range(10000000))").collect()
> {code}
> takes 7 seconds, while
> {code}
> sql("select approx_percentile(id, array(0.1)) from range(10000000)").collect()
> {code}
> grinds to a halt - processes the first million rows quickly, and then slows
> down to a few thousands rows / second (4m rows processed after 20 minutes).
> Thread dumps show that it spends time in QuantileSummary.compress.
> Seems it hits some edge case inefficiency when dealing with sorted data?
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