jsoniter-scala VS 1brc

What an amazing step by step explanation!

More than 2 years ago I found that byte array view var handles are quite suitable to cook efficient SWAR routines with Java/Scala.

See a lot of other examples of SWAR usage, like parsing Base16/64 string, java.time.* and number values directly from byte arrays:

https://github.com/plokhotnyuk/jsoniter-scala/blob/master/js...

Afaik dsl-json came up with a lot of improvements and inspired a several other libraries like JsonIter and jsonIter-scala. Jsoniter-scala by u/plokhotnyuk is probably the most optimized JSON library on the JVM at this point, and seems to power most of the Scala ecosystem. Some implementations/optimizations eventually made their way back into Jackson and other libraries.

I was on your place more then 5 years ago, when cut the 1st release of jsoniter-scala.

I've just increased compiler performance in ~1.5x times by adding these JVM options for the code cache

We have our own open-source code-generator that produces Scala code from Smithy. The code module is entirely dependency-free, and the generated code is not biased towards any library, be that http or json. We do however have out-of-the-box integration with jsoniter and http4s.

You can use jsoniter-scala. It is easy to use like upickle.

BTW, jsoniter-scala uses it for faster parsing and serialization using SWAR techniques, like here.

Probably you should have both codecs (for Foo and for its T) are implicitly available in the scope, like it is done in the following test for jsoniter-scala:

BEWARE: uJson is vulnerable under DoS attacks

Please see sources (and GitHub history of development) of jsoniter-scala as an example in the domain of JSON parsing and serialization.

This would be the code to beat. Ideally with only 8 cores but any number of cores is also very interesting.

https://github.com/gunnarmorling/1brc/discussions/710

Given that 1-billion-line-file is approximately 13GB, instead of providing a fixed database, the official repository offers a script to generate synthetic data with random readings. Just follow the instructions to create your own database.

Local disk I/O is no longer the bottleneck on modern systems: https://benhoyt.com/writings/io-is-no-longer-the-bottleneck/

In addition, the official 1BRC explicitly evaluated results on a RAM disk to avoid I/O speed entirely: https://github.com/gunnarmorling/1brc?tab=readme-ov-file#eva... "Programs are run from a RAM disk (i.o. the IO overhead for loading the file from disk is not relevant)"

You may have heard of the "The One Billion Row Challenge" (1brc) and in case you don't, go checkout Gunnar Morlings's 1brc repo.

Here’s a thread on results with duckdb, I don’t mean to discourage you taking a shot at all though: https://github.com/gunnarmorling/1brc/discussions/39

If you are in “javaland” look at billion row challenge, you will learn a lot - https://github.com/gunnarmorling/1brc

Even manual vectorization is pain...writing ASM, really?

Rust has unstable portable SIMD and a few third-party crates, C++ has that as well, C# has stable portable SIMD and a very small BLAS-like library on top of it (hell it even exercises PackedSIMD when ran in a browser) and Java is getting stable Panama vectors some time in the future (though the question of codegen quality stands open given planned changes to unsafe API).

Go among these is uniquely disadvantaged. And if that's not enough, you may want to visit 1Brc's challenge discussions and see that Go struggles get anywhere close to 2s mark with both C# and C++ are blazing past it:

https://hotforknowledge.com/2024/01/13/1brc-in-dotnet-among-...

https://github.com/gunnarmorling/1brc/discussions/67

In terms of performance: I realize that this is a somewhat "toy" issue, and it's a sample size of 1, but for the currently ongoing "One Billion Row Challenge"[1] (an ongoing Java performance competition related to parsing and aggregating a 13 GB file), all of the current top-performers are using Unsafe. More specifically, the use of Unsafe appears to have been the change for a few entries that allowed getting below the 3-second barrier in the test.

1. https://github.com/gunnarmorling/1brc