AwesomeCSV
simdjson
AwesomeCSV | simdjson | |
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1 | 65 | |
658 | 18,538 | |
- | 1.3% | |
3.0 | 9.2 | |
25 days ago | 10 days ago | |
PowerShell | C++ | |
Creative Commons Zero v1.0 Universal | Apache License 2.0 |
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AwesomeCSV
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Why isnāt there a decent file format for tabular data?
One major limitation with quoted values that can this contain record delimiters (as opposed to escaping the delimiters) is that it stops systems from being able to load records in parallel.
Some systems ban embedded record delimiters, for this reason.
Btw, Iāve (previously) included at least one of your essays in āawesome csvā list at GitHub. https://github.com/secretGeek/AwesomeCSV#essays
Thereās a few specs mentioned there too ā is one of those the spec you worked on?
simdjson
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Tips on adding JSON output to your command line utility. (2021)
It's also supported by simdjson [0] (which has a lot of language bindings [1]):
> Multithreaded processing of gigantic Newline-Delimited JSON (ndjson) and related formats at 3.5 GB/s
[0] https://simdjson.org/
[0] https://github.com/simdjson/simdjson?tab=readme-ov-file#bind...
- 1BRC Merykitty's Magic SWAR: 8 Lines of Code Explained in 3k Words
- Training great LLMs from ground zero in the wilderness as a startup
- simdjson: Parsing Gigabytes of JSON per Second
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Use any web browser as GUI, with Zig in the back end and HTML5 in the front end
String parsing is negligible compared to the speed of the DOM which is glacially slow: https://news.ycombinator.com/item?id=38835920
Come on, people, make an effort to learn how insanely fast computers are, and how insanely inefficient our software is.
String parsing can be done at gigabytes per second: https://github.com/simdjson/simdjson If you think that is the slowest operation in the browser, please find some resources that talk about what is actually happening in the browser?
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Cray-1 performance vs. modern CPUs
Thanks for all the detailed information! That answers a bunch of my questions and the implementation of strlen is nice.
The instruction I was thinking of is pshufb. An example āweirdā use can be found for detecting white space in simdjson: https://github.com/simdjson/simdjson/blob/24b44309fb52c3e2c5...
This works as follows:
1. Observe that each ascii whitespace character ends with a different nibble.
2. Make some vector of 16 bytes which has the white space character whose final nibble is the index of the byte, or some other character with a different final nibble from the byte (eg first element is space =0x20, next could be eg 0xff but not 0xf1 as that ends in the same nibble as index)
3. For each block where you want to find white space, compute pcmpeqb(pshufb(whitespace, input), input). The rules of pshufb mean (a) non-ascii (ie bit 7 set) characters go to 0 so will compare false, (b) other characters are replaced with an element of whitespace according to their last nibble so will compare equal only if they are that whitespace character.
Iām not sure how easy it would be to do such tricks with vgather.vv. In particular, the length of the input doesnāt matter (could be longer) but the length of white space must be 16 bytes. Iām not sure how the whole vlen stuff interacts with tricks like this where you (a) require certain fixed lengths and (b) may have different lengths for tables and input vectors. (and indeed there might just be better ways, eg you could imagine an operation with a 256-bit register where you permute some vector of bytes by sign-extending the nth bit of the 256-bit register into the result where the input byte is n).
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Codebases to read
Additionally, if you like low level stuff, check out libfmt (https://github.com/fmtlib/fmt) - not a big project, not difficult to understand. Or something like simdjson (https://github.com/simdjson/simdjson).
- Simdjson: Parsing Gigabytes of JSON per Second
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Building a high performance JSON parser
Everything you said is totally reasonable. I'm a big fan of napkin math and theoretical upper bounds on performance.
simdjson (https://github.com/simdjson/simdjson) claims to fully parse JSON on the order of 3 GB/sec. Which is faster than OP's Go whitespace parsing! These tests are running on different hardware so it's not apples-to-apples.
The phrase "cannot go faster than this" is just begging for a "well ackshully". Which I hate to do. But the fact that there is an existence proof of Problem A running faster in C++ SIMD than OP's Probably B scalar Go is quite interesting and worth calling out imho. But I admit it doesn't change the rest of the post.
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New package : lspce - a simple LSP Client for Emacs
I have same question as /u/JDRiverRun : how do you deal with JSON, do you parse json on Rust side or on Emacs side. I see that you are requiring json.el in your lspce.el, but I haven't looked through entire file carefully. If you parse on Rust side, do you use simdjson (there are at least two Rust bindings to it)? If yes, what are your impressions, experiences compared to more "standard" json library?
What are some alternatives?
parquet-wasm - Rust-based WebAssembly bindings to read and write Apache Parquet data
RapidJSON - A fast JSON parser/generator for C++ with both SAX/DOM style API
odiff - The fastest pixel-by-pixel image visual difference tool in the world.
jsoniter - jsoniter (json-iterator) is fast and flexible JSON parser available in Java and Go
steam2csv - View and download anyone's Steam game library to a .csv file
json - JSON for Modern C++
catsql - cat for sql dbs
json-schema-validator - JSON schema validator for JSON for Modern C++
ssv - Separator Separated Values file format and libraries
JsonCpp - A C++ library for interacting with JSON.
rson - Rust Object Notation
json - A C++11 library for parsing and serializing JSON to and from a DOM container in memory.