Tin Vu created SPARK-23797:
------------------------------
Summary: 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
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,
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]