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Posted to issues@spark.apache.org by "Ramakrishna (Jira)" <ji...@apache.org> on 2022/11/28 12:40:00 UTC

[jira] [Updated] (SPARK-41298) Getting Count on data frame is giving the performance issue

     [ https://issues.apache.org/jira/browse/SPARK-41298?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Ramakrishna updated SPARK-41298:
--------------------------------
    Description: 
We are invoking  below query on Teradata 

1) Dataframe<Row> df = spark.format("jdbc"). . . load();

2) int count = df.count();

When we executed the df.count spark internally issuing the below query on teradata which is wasting the lot of CPU on teradata and DBAs are making noise by seeing this query.

 

Query : SELECT 1 FROM (<ONE_MILLION_ROWS_TABLE>)SPARK_SUB_TAB

Response:

1

1

1

1

1

..

1

 

Is this expected behavior from spark or is it bug.

  was:
We are invoking  below query on Teradata 

1) Dataframe<Row> df = spark.format("jdbc"). . . load();

2) int count = df.count();

When we executed the df.count spark internally issuing the below query on teradata which is wasting the lot of CPU on teradata and DBAs are making noise by seeing this query.

 

Query : SELECT 1 FROM (<ONE_MILLION_ROWS_TABLE>)SPARK_SUB_TAB

Response:

1

1

1

1

1

..

1

 

Is this expected behavior form spark.


> Getting Count on data frame is giving the performance issue
> -----------------------------------------------------------
>
>                 Key: SPARK-41298
>                 URL: https://issues.apache.org/jira/browse/SPARK-41298
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.4.4
>            Reporter: Ramakrishna
>            Priority: Major
>
> We are invoking  below query on Teradata 
> 1) Dataframe<Row> df = spark.format("jdbc"). . . load();
> 2) int count = df.count();
> When we executed the df.count spark internally issuing the below query on teradata which is wasting the lot of CPU on teradata and DBAs are making noise by seeing this query.
>  
> Query : SELECT 1 FROM (<ONE_MILLION_ROWS_TABLE>)SPARK_SUB_TAB
> Response:
> 1
> 1
> 1
> 1
> 1
> ..
> 1
>  
> Is this expected behavior from spark or is it bug.



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