comprehensive-rust VS datafusion-ballista

Thanks! We do include speaker notes on some pages (but not yet all[1]). We would love to expand this and PRs are very welcome for this :-)

I think videos will end up being made by someone other than me since I feel it takes too much effort when you don't have the right setup already. We have an issue and I'll update it as soon as I hear more about videos.[2]

[1]: https://github.com/google/comprehensive-rust/issues/1083

A bit more detail: we've been expanding our Rust training at Google over the last year. We've now had more than 500 Googlers go through Comprehensive Rust and they tell us that they really like it — also when we ask them again three months later :-)

The post is a huge Thank You! to the many people who have helped with the course, both inside and outside of Google. More than 30 Googlers (who already knew Rust) have picked up the course and taught it around the world.

People have used the material for [university classes](https://mo8it.com/blog/teaching-rust/) and there will soon be [online classes](https://twitter.com/mrtngslr/status/1696601520412783052) as well. I hope it will become a good resource for people to teach Rust in many different contexts!

Pull requests are always welcome, the whole thing is open source: https://github.com/google/comprehensive-rust/.

Yes, I would love to have more contributors to https://github.com/google/comprehensive-rust and https://github.com/google/mdbook-i18n-helpers!

That's done with a bit of JavaScript. It's not super elegant... I would love to have someone with current JavaScript skills improve it :D

Not super on topic because this is all immature and not integrated with one another yet, but there is a scaled-out rust data-frames-on-arrow implementation called ballista that could maybe? form the backend of a polars scale out approach: https://github.com/apache/arrow-ballista

> Is Rust's compile-time GC about something other than performance somehow?

AFAIK, memory safety and language features as RAII is also available in C++, for instance. About the reasons for slow compilation, take a look at https://www.reddit.com/r/rust/comments/xna9mb/why_are_rust_p...

Not having a GC is also about not having a runtime as you mention (e.g. nice for creating Python extensions and embedded systems programming) and also more runtime deterministic performance: on that, if I'm not mistaken that was the reason for Discourse switching to Rust and also, e.g.: "the choice of Rust as the main execution language avoids the overhead of GC pauses and results in deterministic processing times" https://github.com/apache/arrow-ballista/blob/main/README.md

Ballista (Arrow-Rust), which is largely inspired by Apache Spark, there are some interesting differences.

https://github.com/jorgecarleitao/arrow2 https://github.com/apache/arrow-datafusion https://github.com/apache/arrow-ballista https://github.com/pola-rs/polars https://github.com/duckdb/duckdb

Source: https://github.com/apache/arrow-ballista

Can you explain how this might differ from something like https://github.com/apache/arrow-ballista

I've seen several variants of "next-gen" spark, but nowhere have I really seen the different tradeoffs/advantages/disadvantages between them.

Rust has amazing integration with Python through PyO3 [1] so see it like a safe alternative for high performance calculations. The ecosystem itself is starting to come together exciting projects like Polars [2] (Pandas alternative), nalgebra [3], Datafusion [4] and Ballista [5]

[1] https://github.com/PyO3/pyo3

[2] https://github.com/pola-rs/polars/

[3] https://docs.rs/nalgebra/latest/nalgebra/

[4] https://github.com/apache/arrow-datafusion

[5] https://github.com/apache/arrow-ballista