arrow-rs VS miri

https://github.com/djkoloski/rust_serialization_benchmark

Apache/arrow-rs: https://github.com/apache/arrow-rs

From https://arrow.apache.org/faq/ :

> How does Arrow relate to Flatbuffers?

> Flatbuffers is a low-level building block for binary data serialization. It is not adapted to the representation of large, structured, homogenous data, and does not sit at the right abstraction layer for data analysis tasks.

> Arrow is a data layer aimed directly at the needs of data analysis, providing a comprehensive collection of data types required to analytics, built-in support for “null” values (representing missing data), and an expanding toolbox of I/O and computing facilities.

> The Arrow file format does use Flatbuffers under the hood to serialize schemas and other metadata needed to implement the Arrow binary IPC protocol, but the Arrow data format uses its own representation for optimal access and computation

One of the interesting components of Polars that I've been watching is the use of the Apache Arrow memory format, which is a standard layout for data in memory that enables processing (querying, iterating, calculating, etc) in a language agnostic way, in particular without having to copy/convert it into the local object format first. This enables cross-language data access by mmaping or transferring a single buffer, with zero [de]serialization overhead.

For some history, there's has been a bit of contention between the official arrow-rs implementation and the arrow2 implementation created by the polars team which includes some extra features that they find important. I think the current status is that everyone agrees that having two crates that implement the same standard is not ideal, and they are working to port any necessary features to the arrow-rs crate and plan on eventually switching to it and deprecating arrow2. But that's not easy.

https://github.com/apache/arrow-rs/issues/1176

https://github.com/jorgecarleitao/arrow2/pull/1476

It's built around the arrow-rs library, which we've contributed to significantly: https://github.com/apache/arrow-rs

For loading Parquet in memory, probably worth a look at arrow-rs.

From what I've seen, most of the Rust community seems to be adopting Apache Arrow as the go-to for data processing. It has strong community support and good interoperability with many cross-language tools. It is natively a columnar format. If row-oriented is a must for your use case, consider looking into alternatives like gRPC that might better suit your needs.

That matrix doesn't seem up to date. For example looking at the rust crate it does seem to support things like map, float16, and IPC. The changelog shows an impressive development pace.

Oh, and for anyone interested in pitching in on the Rust implementation, there's an issue logged here along with some discussion: https://github.com/apache/arrow-rs/issues/1323

There is more discussion about the decision here: https://github.com/apache/arrow-rs/issues/1120

I'm still not sure how this differs from https://github.com/apache/arrow-rs. What does transmute even mean?

>While we are many missing language features away from this being the case, the noalias case is also magic descended upon box itself, with no user code ever having access to it.

I'm not sure why the author thinks there's magic behind Box. Box is not a special case of `noalias`. Run this snippet with miri and you'll see the same issue: https://play.rust-lang.org/?version=stable&mode=debug&editio...

`Box` _does_ have an expectation that its inner pointer is not aliased to another Box (even if used for readonly operations). See: https://github.com/rust-lang/miri/issues/1800#issuecomment-8...)

Miri [0] is an interpreter for the mid-level intermediate representation (MIR) generated by the Rust compiler. MIR is input for more processing steps of the compiler. However miri also runs MIR directly. This means miri is a VM. Of course it's not a bytecode VM, because MIR is not a bytecode AFAIK. I still think that miri is a interesting example.

And why does miri exist?

It is a lot slower. However it can check for some undefined behavior.

[0]: https://github.com/rust-lang/miri

Provenance is a dynamic property of pointer values. The actual underlying rules that a program must follow, even when using raw pointers and `unsafe`, are written in terms of provenance. Miri (https://github.com/rust-lang/miri) represents provenance as an actual value stored alongside each pointer's address, so it can check for violations of these rules.

Lifetimes are a static approximation of provenance. They are erased after being validated by the borrow checker, and do not exist in Miri or have any impact on what transformations the optimizer may perform. In other words, the provenance rules allow a superset of what the borrow checker allows.

There has been discussion of doing this with MIRI, which would be easier than all of rustc.

This issue has been fixed: https://github.com/rust-lang/miri/issues/2964

Actually, I've done more advanced tests with MIRI (see https://github.com/rust-lang/miri/issues/2920 for example) which allowed me to fix some issues. I've also made the code compatible with loom, but I didn't found the time yet to write and execute loom tests. That's on the TODO-list, and I need to track it with an issue too.

He is one of the big brains behind Miri, which is a interpreter that runs on the MIR (compiler representation between human code and asm/machine code) and detects undefined behavior. Super useful tool for language safety, pretty interesting on its own.

I would also run your tests in Miri (https://github.com/rust-lang/miri) to try to cover more bases.