[jira] [Resolved] (SPARK-41070) Performance issue when Spark SQL connects with TeraData

["Hyukjin Kwon (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-41070?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-41070.
----------------------------------
    Resolution: Invalid

> Performance issue when Spark SQL connects with TeraData 
> --------------------------------------------------------
>
>                 Key: SPARK-41070
>                 URL: https://issues.apache.org/jira/browse/SPARK-41070
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core, SQL
>    Affects Versions: 2.4.4
>            Reporter: Ramakrishna
>            Priority: Major
>
> We are connecting Tera data from spark SQL with below API
> {color:#ff8b00}Dataset<Row> jdbcDF = spark.read().jdbc(connectionUrl, tableQuery, connectionProperties);{color}
> We are facing one issue when we execute above logic on large table with million rows every time we are seeing below extra query is executing every time as this resulting performance hit on DB.
> This below information we got from DBA. We dont have any logs on SPARK SQL.
> SELECT 1 FROM ONE_MILLION_ROWS_TABLE;
> |1|
> |1|
> |1|
> |1|
> |1|
> |1|
> |1|
> |1|
> |1|
> |1|
>  
> Can you please clarify why this query is executing or is there any chance that this type of query is executing from our code it self while check for rows count from dataframe.
>  
> Please provide me your inputs on this.
>  



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