rust_serialization_benchmark VS rkyv

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

Nice that comfy gets even easier. Also, if serde's compile time is an issue, then there's nanoserde which is usually much much faster according to benchmarks

A note on performance and size: Some benchmarks and statistics are included in the README. But only because people will be curious. I've based my methodology on rust_serialization_benchmark, but decided to not extend it (for now) since it seems to exclude any Rust types which are not widely supported by all formats being tested (like HashMap's and 128-bit numbers). The test suite is already quite nice if you want to take it for a spin.

While we haven't benchmarked either of those ourselves. You can checkout rust_serialization_benchmark which has protobuf under the name prost.

Update: Benchmark PR submitted: https://github.com/djkoloski/rust_serialization_benchmark/pull/37

Here is a speed and size benchmark of different rust binary serialization formats: https://github.com/djkoloski/rust_serialization_benchmark Warning: I think the creator of this benchmark is also the creator of rkyv, one of the best positioned formats in the benchmark.

So I assume you're deserializing them before processing the book? If so then if you want an easy speed-up you could also take a look at these benchmarks and pick a faster serialization crate. (: (Although you might or might not get a big speedup; depends on what exactly you're deserializing and how much you are deserializing.)

You can add the rust serialization benchmark to that list

Hey! Similar to bincode, it provides a very similar, compact binary format. The rkyv benchmark is the most comprehensive I'm aware of, but compared to bincode, postcard is generally a similar speed for serialization or deserialization (maybe a touch slower), but generally produces a slightly smaller "on the wire" size.

You should add your crate to these benchmarks. (Which are, AFAIK, the most comprehensive set of benchmarks currently available for Rust serialization libraries.)

And before you ask: This only provides partial zero-copy support in strings and byte arrays like serde. But it's not like rkyv which constructs validated references into the data.

Regarding JSON, what kind of other implementation do you have in mind? I've seen e.g. `rkyv` which looks really neat (https://github.com/rkyv/rkyv/issues/85). So far `serde_json` is providing a clean surface API but maybe there's best solution?

Thank you for your concern. I've done plenty of projects that go beyond a "Hello World" such as a GPU accelerated password cracker. I am starting soon a C++/Rust job. I already contributed to codebases I didn't write.

rkyv is awesome because it supports full zero-copy deserialization. You can serialize your HashMap to a file. Later you can directly use the HashMap from the file without creating and populating a new HashMap in memory (rkyv directly indexes into the raw bytes). For even faster access times you can even mmap the file.

I had the same problem when trying to deserialize a big struct with rkyv: see rkyv#277.

Any chance of working with zero-copy deserialization frameworks? like https://github.com/rkyv/rkyv or capnproto

Hi, you seem to know a bit about Sanakirja!

It stores 4kb blobs, right? Does Pijul first parses the data (copying it to other allocations), or uses the data as is? I mean, there are some libraries like cap'n'proto[0] and rkyv[1] that can directly use the file contents as an in-memory data structure, I was wondering if Pijul did anything like that.

I mean, is this btree page [2] stored exactly like this on disk, and does Pijul exploits that to avoid further copying data?

(I guess there's a trouble with compression there: to decompress you really need to write in another buffer)

Also, is the I/O done with something that prevent userspace copies like mmap or io_uring, or does it eventually calls read() to copy the data to its own buffer?

I want to build something like Sanakirja, but with those features, so I'm wondering if there's any overlap.

[0] https://github.com/capnproto/capnproto-rust

[1] https://github.com/rkyv/rkyv

[2] https://docs.rs/sanakirja-core/latest/sanakirja_core/btree/p...

I think https://github.com/rkyv/rkyv does this. Also capnproto like was mentioned here, and perhaps https://docs.rs/zerocopy/0.6.1/zerocopy/index.html too

It's been two months since the last major rkyv release, and three months since the last major feature release. After all that time, I'm proud to announce that rkyv 0.7 is finally out!

After roughly two months of work, rkyv 0.5 is finally out!