-
Notifications
You must be signed in to change notification settings - Fork 1.9k
Run TPC-H SF10 during PR benchmarks #9822
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Conversation
| # Setup the TPC-H data set with a scale factor of 10 | ||
| # Setup the TPC-H data sets for scale factors 1 and 10 | ||
| ./bench.sh data tpch |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Does it make sense to do SF=1?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Fair point; I guess it can be beneficial to detect minor systemic/non-linear regressions that are larger than the noise level, but smaller then the sensitivity of SF 10?
| cd benchmarks | ||
| ./bench.sh run tpch | ||
| ./bench.sh run tpch10 |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Perhaps we could run tpch10_mem as well if it doesn't run OOM, or tpch_mem otherwise which should have less variance.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Yeah I can add tpch10_mem as well.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Ok I've added both tpch_mem10 and tpch_mem, so that we can observe and compare the noise level for each one.
Also distinguish the output file by the SF used.
* Run TPC-H SF10 during PR benchmarks * Add memory benchmarks to the workflow Also distinguish the output file by the SF used.
Which issue does this PR close?
Progresses #5504.
Rationale for this change
Make the variance a smaller component in benchmarks by using a larger SF
and thus reduce the noise/false-positives.
What changes are included in this PR?
Run SF 10 in PR benchmarks too.
Are these changes tested?
Are there any user-facing changes?