json-benchmark VS rust_serialization_benchmark

I don’t really understand what this is trying to prove:

- you don’t seem to specify the size of the input. This is the most important omission

- you are constructing an optimised representation (in this case, strict with fields in the right places) instead of a generic ‘dumb’ representation that is more like a tree of python dicts

- rust is not a ‘moderately fast language’ imo (though this is not a very important point. It’s more about how optimised the parser is, and I suspect that serde_json is written in an optimised way, but I didn’t look very hard).

I found[1], which gives serde_json to a dom 300-400MB/s on a somewhat old laptop cpu. A simpler implementation runs at 100-200, a very optimised implementation gets 400-800. But I don’t think this does that much to confirm what I said in the comment you replied to. The numbers for simd json are a bit lower than I expected (maybe due to the ‘dom’ part). I think my 50MB/a number was probably a bit off but maybe the python implementation converts json to some C object and then converts that C object to python objects. That might half your throughput (my guess is that this is what the ‘strict parse’ case for rustc_serialise is roughly doing).

[1] https://github.com/serde-rs/json-benchmark

But the code OP posted deserializes JSON without knowing anything about the structure, which is known to be slow in serde-json and doesn't appear to be the focus for the library. The json and json-deserializer crates should perform much better in that scenario.

Of course that doesnt mean that in practice the available libraries are as optimized. Did you try actix? It tends to be faster than rocket. Also json-rust and simd-json are usually faster than serde-json, when you don't deserialize a known structure. Here are some benchmarks: https://github.com/serde-rs/json-benchmark

The data for the test is taken from here: https://github.com/serde-rs/json-benchmark/tree/master/data

Here are some benchmarks https://github.com/serde-rs/json-benchmark

I found two projects: * https://github.com/djkoloski/rust_serialization_benchmark - doesn't use Serde zero copy * https://github.com/serde-rs/json-benchmark - has copy vs borrowed, but the results were the same for both, so something's off there

Rust has a good enough standard library (I’d say comparable to C++), that you don’t really need packages for a lot of stuff. Most of my projects have 1 or 2 dependencies. Most of the time I am pulling in a JS parser (serde) and a parallelization library (rayon). These are both high performance libraries that make writing very fast (serde can handle 850 MB/s on a 5 year old laptop cpu per their benchmarks). Rayon is one of the best parallelism libraries I’ve worked with.

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.)