You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Seok-Joon,Yun (JIRA)" <ji...@apache.org> on 2018/04/20 00:40:00 UTC
[jira] [Created] (SPARK-24030) SparkSQL percentile_approx function
is too slow for over 1,060,000 records.
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-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org