Comment by 1a527dd5
10 hours ago
I appreciate performance as much as the next person; but I see this endless battle to measure things in ns/us/ms as performative.
Sure there are 0.000001% edge cases where that MIGHT be the next big bottleneck.
I see the same thing repeated in various front end tooling too. They all claim to be _much_ faster than their counterpart.
9/10 whatever tooling you are using now will be perfectly fine. Example; I use grep a lot in an ad hoc manner on really large files I switch to rg. But that is only in the handful of cases.
Whenever you have this kind of impressions on some development, here are my 2 cents: just think "I'm not the target audience". And that's fine.
The difference between 2ms and 0.2ms might sound unneeded, or even silly to you. But somebody, somewhere, is doing stream processing of TB-sized JSON objects, and they will care. These news are for them.
I remember when I was coming up on the command line and I'd browse the forums at unix.com. Someone would ask how to do a thing and CFAJohnson would come in with a far less readable solution that was more performative (probably replacing calls to external tools with Bash internals, but I didn't know enough then to speak intelligently about it now).
People would say, "Why use this when it's harder to read and only saves N ms?" He'd reply that you'd care about those ms when you had to read a database from 500 remote servers (I'm paraphrasing. He probably had a much better example.)
Turns out, he wrote a book that I later purchased. It appears to have been taken over by a different author, but the first release was all him and I bought it immediately when I recognized the name / unix.com handle. Though it was over my head when I first bought it, I later learned enough to love it. I hope he's on HN and knows that someone loved his posts / book.
https://www.amazon.com/Pro-Bash-Programming-Scripting-Expert...
Wow that takes me back. I used to lurk on unix.com when I was starting with bash and perl and would see CFAJohnson's terse one-liners all the time. I enjoyed trying my own approaches to compare performance, conciseness and readability - mainly for learning. Some of the awk stuff was quite illuminating in my understanding of how powerful awk could be. I remember trying different approaches to process large files at first with awk and then with Perl. Then we discovered Oracle's external tables which turned out to be clear winner. We have a lot more options now with fantastic performance.
Also as someone who looks at latency charts too much, what happens is a request does a lot in series and any little ms you can knock off adds up. You save 10ms by saving 10 x 1ms. And if you are a proxyish service then you are a 10ms in a chain that might be taking 200 or 300ms. It is like saving money, you have to like cut lots of small expenses to make an impact. (unless you move etc. but once you done that it is small numerous things thay add up)
Also performance improvements on heavy used systems unlocks:
Cost savings
Stability
Higher reliability
Higher throughput
Fewer incidents
Lower scaling out requirements.
Wait what? I don't get why performance improvement implies reliability and incident improvement.
For example, doing dangerous thing might be faster (no bound checks, weaker consistency guarantee, etc), but it clearly tend to be a reliability regression.
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Which is fine, but the vast majority of the things that get presented aren’t bothering to benchmark against my use (for a whole lotta mes). They come from someone scratching an itch and solving it for a target audience of one and then extrapolating and bolting on some benchmarks. And at the sizes you’re talking about, how many tooling authors have the computing power on hand to test that?
> "somebody, somewhere, is doing stream processing of TB-sized JSON objects"
That's crazy to think about. My JSON files can be measured in bytes. :-D
Well obviously that would happen mostly only on the biggest business scales or maybe academic research; one example from Nvidia, which showcases Apache Spark with GPU acceleration to process "tens of terabytes of JSON data":
https://developer.nvidia.com/blog/accelerating-json-processi...
All files can be measured in bytes. :)
But even in this example, the 2ms vs 0.2 is irrelevant - its whatever the timings are for TB-size objects.
So went not compare that case directly? We'd also want to see the performance of the assumed overheads i.e. how it scales.
Who is the target audience? I truly wonder who will process TB-sized data using jq? Either it's in a database already, in which case you're using the database to process the data, or you're putting it in a database.
Either way, I have really big doubts that there will be ever a significant amount of people who'd choose jq for that.
There was a thread yesterday where a company rewrote a similar JSON processing library in Go because they were spending $100,000s on serving costs using it to filter vast amounts of data: https://news.ycombinator.com/item?id=47536712
I get the sentiment, but everybody thinks that, and in aggregate, you get death by a thousand paper cuts.
It’s the same sentiment as “Individuals don’t matter, look at how tiny my contribution is.”. Society is made up of individuals, so everybody has to do their part.
> 9/10 whatever tooling you are using now will be perfectly fine.
It is not though. Software is getting slower faster than hardware is getting quicker. We have computers that are easily 3–4+ orders of magnitudes faster than what we had 40 years ago, yet everything has somehow gotten slower.
True. I feel like the main way a tool could differentiate from jq is having more intuitive syntax and many real world examples to show off the syntax.
For better or worse, Claude is my intuitive interface to jq. I don't use it frequently, and before I would have to look up the commands every time, and slowly iterate it down to what I needed.
The syntax makes perfect sense when you understand the semantics of the language.
Out of curiosity, have you read the jq manpage? The first 500 words explain more or less the entire language and how it works. Not the syntax or the functions, but what the language itself is/does. The rest follows fairly easily from that.
Was about to post exactly this... It is impressive engineering wise, but for data and syntax, ease of use or all the great features, I care about that more. Speed isn't that important to me for a lot of these tools.
If I/you was working with JSON of that size where this was important, id say you probably need to stop using JSON! and some other binary or structured format... so long as it has some kinda tooling support.
And further if you are doing important stuff in the CLI needing a big chain of commands, you probably should be programming something to do it anyways...
that's even before we get to the whole JSON isn't really a good data format whatsoever... and there are many better ways. The old ways or the new ways. One day I will get to use my XSLT skills again :D
I agree for some things, but not for tools or "micro-software" like jq that can get called a LOT in an automated process. Every order of magnitude saved for the latter category can be meaningful.
Maybe look at it from another perspective. Better performance == less CPU cycles wasted. Consider how many people use jq daily and think about how much energy could be saved by faster implementations. In times like this where energy is becoming more scarce we should think about things like this.
I agree, but in this age of widespread LLM use, that's only marginal.
> Consider how many people use jq daily and think about how much energy could be saved by faster implementations.
Say a number; make a real argument. Don't just wave your hand and say "just imagine how right I could be about this vague notion if we only knew the facts"
Then this is for the handful of cases for you. When it matters it matters.
Yes
I don't think I remember one case where jq wasn't fast enough
Now what I'd really want is a jq that's more intuitive and easier to understand
> Now what I'd really want is a jq that's more intuitive and easier to understand
Unfortunately I don’t recall the name, but there was something submitted to HN not too long ago (I think it was still 2026) which was like jq but used JavaScript syntax.
> I see the same thing repeated in various front end tooling too. They all claim to be _much_ faster than their counterpart.
>> 9/10 whatever tooling you are using now will be perfectly fine
Are you working in frontend? On non-trivial webapps? Because this is entirely wrong in my experience. Performance issues are the #1 complaint of everyone on the frontend team. Be that in compiling, testing or (to a lesser extend) the actual app.
Worked on front end for years. Rarely ever hear people talking about performance issues. I was among the very few people who knew how to use the dev tools to investigate memory leak or heard of memlab.
Either the team I worked at was horrible, or you are from Google/Meta/Walmart where either everyone is smart or frondend performance is directly related to $$.
"performance is directly related to $$"
It is. Company size is moot. See https://wpostats.com for starters.
There are some really fast tools out there for compiling FE these days, and that's probably to what they refer. Testing is still a slog.
Uh, I've worked for a few years as a frontend dev, as in literal frontend dev - at that job my responsibility started at consuming and ended at feeding backend APIs, essentially.
From that I completely agree with your statement - however, you're not addressing the point he makes which kinda makes your statement completely unrelated to his point
99.99% of all performance issues in the frontend are caused by devs doing dumb shit at this point
The frameworks performance benefits are not going to meaningfully impact this issue anymore, hence no matter how performant yours is, that's still going to be their primary complaint across almost all complex rwcs
And the other issue is that we've decided that complex transpiling is the way to go in the frontend (typescript) - without that, all built time issues would magically go away too. But I guess that's another story.
It was a different story back when eg meteorjs was the default, but nowadays they're all fast enough to not be the source of the performance issues
Fair, but agentic tooling can benefit quite a lot from this
Opencode, ClaudeCode, etc, feel slow. Whatever make them faster is a win :)
The 2ms it takes to run jq versus the 0.2ms to run an alternative is not why your coding agent feels slow.
Still, jq is run a whole lot more than it used to be due to coding agents, so every bit helps.
The vast majority of Linux kernel performance improvement patches probably have way less of a real world impact than this.
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It's not running jq locally that's causing that