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https://issues.apache.org/jira/browse/SPARK-23797?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-23797.
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    Resolution: Incomplete

> SparkSQL performance on small TPCDS tables is very low when compared to Drill 
> or Presto
> ---------------------------------------------------------------------------------------
>
>                 Key: SPARK-23797
>                 URL: https://issues.apache.org/jira/browse/SPARK-23797
>             Project: Spark
>          Issue Type: Bug
>          Components: Optimizer, Spark Submit, SQL
>    Affects Versions: 2.3.0
>            Reporter: Tin Vu
>            Priority: Major
>              Labels: bulk-closed
>
> I am executing a benchmark to compare performance of SparkSQL, Apache Drill 
> and Presto. My experimental setup:
>  * TPCDS dataset with scale factor 100 (size 100GB).
>  * Spark, Drill, Presto have a same numberĀ of workers: 12.
>  * Each worked has same allocated amount of memory: 4GB.
>  * Data is stored by Hive with ORC format.
> I executed a very simple SQL query: "SELECT * from table_name"
>  The issue is that for some small size tables (even table with few dozen of 
> records), SparkSQL still required about 7-8 seconds to finish, while Drill 
> and Presto only needed less than 1 second.
>  For other large tables with billions records, SparkSQL performance was 
> reasonable when it required 20-30 seconds to scan the whole table.
>  Do you have any idea or reasonable explanation for this issue?
> Thanks,



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