ndjson-spec VS simdjson

What’s the difference between terminators and separators here? The ndjson spec [0] doesn’t say anything like that, and it seems that ndjson and jsonlines are identical in what documents they accept.

[0]: https://github.com/ndjson/ndjson-spec

It's possible to work around this and still use a JSON-ish format. For example, my @broofa/persistentmap project provides an ES6 Map API backed by a persistent append-only file in NDJSON format. (Note: NDJSON isn't really a spec so much as a "convention"). But, honestly,

ndjson is actually a really pragmatic choice here that should not be overlooked.

Tabular formats break down when the data stops being tabular. This comes up a lot. People love spread sheets as editing tools but they then end up doing things like putting comma separated values in a cell. I've also seen business people use empty cells to indicate hierarchical 'inheritance". An alternate interpretation of that is that that data has some kind of hierarchy and isn't really row based. People just shoehorn all sorts of stuff into spreadsheets because they are there.

With ndjson, every line is a json object. Every cell is a named field. If you need multiple values, you can use arrays for the fields. Json has actual types (int, float, strings, boolean). So you can have both hierarchical and multivalued data in a row. The case where all the fields are simple primitives is just the simple case. It has an actual specification too: https://github.com/ndjson/ndjson-spec. I like it because I can stream process it and represent arbitrarily complex objects/documents instead of having to flatten it into columns. The parsing overhead makes it more expensive to use than tsv though. The file size is fine if you use e.g. gzip compression. It compresses really well generally.

But I also use either tab separated values quite often for simpler data. I mainly like it because google spread sheets provides that as an export option and is actually a great editor for tabular data that I can just give to non technical people.

Both file formats can be easily manipulated with command line tools (jq, csvkit, sed, etc.). Both can be processed using mature parsers in a wide range of languages. If you really want, you can edit them with simple text editors, though you probably should be careful with that. Tools like bat know how to format and highlight these files as well. Etc. Tools like that are important because you can use them and script them together rather than reinventing wheels.

Formats like parquet are cumbersome mainly because none of the tools I mention support it. No editors. Not a lot of command line tools. No formatting tools. If you want to inspect the data, you pretty much have to write a program to do it. I guess this would be fixable but people seem to be not really interested in doing that work. Parquet becomes nice when you need to process data at scale and in any case use a lot of specialized tooling and infrastructure. Not for everyone in other words.

Character encoding is not an issue with either tsv or ndjson if you simply use UTF-8, always. I see no good technical reason why you should use anything else. Anything else should be treated as a bug or legacy. Of course a lot of data has encoding issues regardless. Shit in, shit out basically. Fix it at the source, if you can.

The last point is actually key because all of the issues with e.g. csv usually start with people just using really crappy tools to produce source data. Switching to a different file format won't fix these issues since you still deal with the same crappy tools that of course do not support this file format. Anything else you could just fix to not suck to begin with. And if you do, it stops being an issue. The problem is when you can't.

Nothing wrong with tsv if you use UTF-8 and a some nice framework that generates properly escaped values and does all the right things. The worst you can say about it is that there are a bit too many choices here and people tend to improvise their own crappy data generation tools with escaping bugs and other issues. Most of the pain is self inflicted. The reason csv/tsv are popular is that you don't need a lot of frameworks / tools. But of course the flipside is that DYI leads to people introducing all sorts of unnecessary issues. Try not to do that.

Newline-separated JSON is pretty close. It's not exactly a "standard" standard like something the IETF defines, but it's pretty easy to work with anyhow.

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...

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?

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 ‘weird’ 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.

I’m not sure how easy it would be to do such tricks with vgather.vv. In particular, the length of the input doesn’t matter (could be longer) but the length of white space must be 16 bytes. I’m 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).

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).

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.

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?