TPC-DS Benchmark

The TPC is a non-profit organization that provides several benchmarks for databases. The two common benchmarks they provide for Data Warehousing and Analytics are the Decision Support (TPC-DS) and Ad-Hoc (TPC-H) benchmarks. More information can be found here:

SQL on Hadoop
HAWQ can execute all 99 queries without modification.
– IBM Big SQL can execute all 99 queries but requires modifying 12 queries (as of the most recent publication I can find).
– Impala can’t run all of the queries and many require modifications to execute.
– Hive can’t run all of the queries and many require modifications to execute.

There isn’t much point to compare HAWQ with these other SQL engines when none can execute all of the queries without modification! So… this post will focus on the capabilities of HAWQ as well as the automated TPC-DS benchmark process I have put together.

The tests will use a Hortonworks 2.2 Sandbox with 8GB of RAM and 4 cores dedicated to the VM. The dataset will be 2GB in size which works well in a VM. This is definitely not a huge test but it will demonstrate the capabilities of HAWQ. Again, all 99 queries can run in HAWQ without any modification!

I’m using the tests provided here: which I put together to help evaluate different hardware platforms. This script works with HAWQ and with Greenplum database.

This script automates the entire process of generating the data, building the tables, loading the tables, and executing the TPC-DS queries.

1. Compile TPC-DS: 3.4 seconds
2. Generate the Data using dsdgen: 3 minutes 23 seconds
3. Create tables and ensure correct optimizer settings are enabled: 5.5 seconds
4. Load the tables: 2 minutes and 5 seconds
5. Execute all 99 TPC-DS queries: 6 minutes 46 seconds


To put this into perspective, I attempted to run a 2GB TPC-DS benchmark in the same VM with another SQL on Hadoop tool and it took 2 hours to just get all of the data loaded! The engine was unable to execute the vendor provided SQL queries either so I gave up on that effort. HAWQ is the way to go!

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