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Posted to issues@spark.apache.org by "Seok-Joon,Yun (JIRA)" <ji...@apache.org> on 2018/04/20 14:18:00 UTC
[jira] [Updated] (SPARK-24030) SparkSQL percentile_approx function
is too slow for over 1,060,000 records.
[ https://issues.apache.org/jira/browse/SPARK-24030?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Seok-Joon,Yun updated SPARK-24030:
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Attachment: screenshot_2018-04-20 23.15.02.png
> SparkSQL percentile_approx function is too slow for over 1,060,000 records.
> ---------------------------------------------------------------------------
>
> Key: SPARK-24030
> URL: https://issues.apache.org/jira/browse/SPARK-24030
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.1
> Environment: zeppline + Spark 2.2.1 on Amazon EMR and local laptop.
> Reporter: Seok-Joon,Yun
> Priority: Major
> Attachments: screenshot_2018-04-20 23.15.02.png
>
>
> I used percentile_approx functions for over 1,060,000 records. It is too slow. It takes about 90 mins. So I tried for 1,040,000 records. It take about 10 secs.
> I tested for data reading on JDBC and parquet. It takes same time lengths.
> I wonder that function is not designed for multi worker.
> I looked gangglia and spark history. It worked on one worker.
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