[jira] [Updated] (SPARK-24030) SparkSQL percentile_approx function is too slow for over 1,060,000 records.

2018-04-20 Thread Seok-Joon,Yun (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-24030?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Seok-Joon,Yun updated SPARK-24030:
--
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.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Created] (SPARK-24030) SparkSQL percentile_approx function is too slow for over 1,060,000 records.

2018-04-19 Thread Seok-Joon,Yun (JIRA) 
Seok-Joon,Yun created SPARK-24030:
-

 Summary: 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


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.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org