Skip to content
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

[DISCUSS] Set DataFusion settings for maximum "out of the box" performance #6287

Open
alamb opened this issue May 8, 2023 · 4 comments
Open
Labels
enhancement New feature or request

Comments

@alamb
Copy link
Contributor

alamb commented May 8, 2023

Is your feature request related to a problem or challenge?

I want people's first impression of DataFusion to be "that is very fast" without having to tune parameters

DataFusion has many configuration options that control various performance optimization.

There is a tradeoff between some of these options between faster query execution (for more than linear resource consumption) and pure efficiency.

We have benchmarks such as a tpch runner that typically run with a single core. These are great as performance unit tests in well controlled environments (and avoid task overhead, and other non determinism introduced with multi-core execution), however they don't mimic what users typically run with.

Up to now we have taken a conservative approach and only enabled optimizations by default if they make everything faster. I would like to change our philosophy and optimize for "out of the box" performance

You can see examples of other systems tuning knobs up for performance:

IOx: https://github.com/influxdata/influxdb_iox/blob/ad28ebb7650d1cd21b995ee5b514d8da3580f22b/datafusion_util/src/config.rs#L20-L23

Here is a recent example from https://hussainsultan.com/posts/unbundled-datafusion/

runtime = RuntimeConfig().with_disk_manager_os().with_fair_spill_pool(100000000)
config = (
    SessionConfig()
    .with_create_default_catalog_and_schema(True)
    .with_target_partitions(8)
    .with_information_schema(True)
    .with_repartition_joins(True)
    .with_repartition_aggregations(True)
    .with_repartition_windows(True)
    .with_parquet_pruning(True)
    .set("datafusion.execution.parquet.pushdown_filters", "true")
)

ctx = SessionContext(config, runtime)
ctx.register_parquet("orders", "../../../fanniemae-benchmark/sf10/raw/orders.parquet")

Describe the solution you'd like

I would like to change the ConfigOption defaults to optimize performance in the common case rather than avoid
performance regressions in all cases

Specifically that means:

  1. Repartition always when possible (to increase parallelism by default)
  2. Push down all parquet filters (e.g. Enable parquet page level skipping (page index pruning) by default #4085 and Enable parquet filter pushdown by default #3463)

Describe alternatives you've considered

We can leave the defaults alone and make users change the defaults

Additional context

No response

@alamb alamb added the enhancement New feature or request label May 8, 2023
@alamb
Copy link
Contributor Author

alamb commented May 8, 2023

Here is another example of where we had to finagle settings to make DataFusion fast: #5942

@comphead
Copy link
Contributor

comphead commented May 8, 2023

Another example what I have found is increasing batch size solves some performance troubles related to excessive collection allocation or loops.

I suppose there is also a trouble when the code gets triggered for empty batches, so the code spins CPU but in fact does nothing, I think noticed this behavior couple of times but need to have a good reproduce test to prove it.

@ozankabak
Copy link
Contributor

Thank you @alamb for putting this together. I definitely agree that we should choose the default configuration settings to squeeze maximum performance. OOTB performance is a common blogging subject, and search results that yield to such posts is a big entry to point to the user funnel. We should give users the right impression in terms of where Datafusion stands in terms of the performance.

@alamb
Copy link
Contributor Author

alamb commented May 10, 2023

#6325 is another project to improve the performance out of the box

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

3 participants