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I wonder so often about many new CLI tools whose primary selling point is their speed over other tools. Yet I personally have not encountered any case where a tool like jq feels incredibly slow, and I would feel the urge to find something else.
What do people do all day that existing tools are no longer enough? Or is it that kind of "my new terminal opens 107ms faster now, and I don't notice it, but I simply feel better because I know"?
- They take Rust for performance or FAVORITE_LANG for credentials
- Claude implements small subset of features
- Benchmark subset
- Claim win, profit on showcase
Note: this particular project doesn't have many visible tells, but there's pattern of overdocumentation (17% comment-to-code ratio, >1000 words in README, Claude-like comment patterns), so it might be a guided process.
I still think that the project follows the "subset is faster than set" trend.
We parse JSON responses for dashboards, alerting, etc. Thousands of nodes, depending on the resolution of your monitoring you could see improvements here.
I'll write a one-off shell pipeline to inspect something on 10^5 servers - it will be sent to each of those servers and run once or a handful of times, and the results will be transmitted back and that's that. Kind of a map-reduce shell thing, for ops type tasks.
Sometimes those will actually need to process through a bunch of data unexpectedly.
Sometimes those will be run on a loop - once per second, N per minute (etc), and the results will be used to monitor a situation until a bug is fixed or a spike in load is resolved or a proper monitoring program/metric can be deployed.
Sometimes those are to investigate a pegged CPU and the amortized lower runtime across all the tasks on the CPU is noticable.
We run our machines hot and part of the reason we can do that is being in the habit of choosing lower cost (in cycles) tooling whenever we can. If i can spend a little time and effort learning a tool that saves a bunch of cpu in aggregate, its a win. When the whole company does it, we can spend a lot less on hardware than it costs in engineer time to make these decisions.
Another way of putting it is: its a type of frugality (not cheapness, just spending wisely). If you save a dollar once, its nothing. If you have a habit of saving a dollar every time the opportunity arises, it adds up quickly. By having a habit of choosing more performant tools, you're less likely to hit a case where you wish you did use more performant tools, and are practiced at it when the need arises for pure parsimony and it's less painful.
I was a bit skeptical at first, but after reading more into jsongrep, it's actually very good. Only did a very quick test just now, and after stumbling over slightly different syntax to jq, am actually quite impressed. Give it a try
I learned a number of data processing cli tools: jq, mlr, htmlq, xsv, yq, etc; to name a few. Not to the level of completing advent of code or anything, but good enough for my day to day usage. It was never ending with the amount of formats I needed to extract data from, and the different syntax's. All that changed when I found nushell though, its replaced all of these tools for me. One syntax for everything, breath of fresh air!
Had to spend some efforts to set up completions, also there some small rough edges around commands discoverability, but anyway, much better than the previous oh-my-zsh setup
Ideally, wish it also had a flag to enforce users to write type annotations + compiling scripts as static binaries + a TUI library, and then I'd seriously consider it for writing small apps, but I like and appreciate it in the current state already
+1. I switched to using Nushell as my daily driver around mid-2023 (0.84.0?) and use it in preference to other interactive tools. I do keep at hand jq, yq, and mlr because I need to exchange stuff with colleagues who don't use Nu.
> Jq is a powerful tool, but its imperative filter syntax can be verbose for common path-matching tasks. jsongrep is declarative: you describe the shape of the paths you want, and the engine finds them.
IMO, this isn't a common use case. The comparison here is essentially like Java vs Python. Jq is perfectly fine for quick peeking. If you actually need better performance, there are always faster ways to parse JSON than using a CLI.
Having used `jq` and `yq` (which followed from the former, in spirit), I have never had to complain about performance of the _latter_ which an order of magnitude (or several) _slower_ than the former. So if there's something faster than `jq`, it's laudable that the author of the faster tool accomplished such a goal, but in the broader context I'd say the performance benefit would be required by a niche slice of the userbase. People who analyse JSON-formatted logs, perhaps? Then again, newline-delimited JSON reigns supreme in that particular kind of scenario, making the point of a faster `jq` moot again.
However, as someone who always loved faster software and being an optimisation nerd, hat's off!
Second, some comments on the presentation: the horizontal violin graphs are nice, but all tools have the same colours, and so it's just hard to even spot where jsongrep is. I'd recommend grouping by tool and colour coding it. Besides, jq itself isn't in the graphs at all (but the title of the post made me think it would be!).
Last, xLarge is a 190MiB file. I was surprised by that. It seems too low for xLarge. I daily check 400MiB json documents, and sometimes GiB ones.
Hey thank you! OP here, yes I was struggling to find large enough documents to run the benchmarks on, the range currently on the benchmark data is ~106 B - ~190MB, which I think covers the majority of quick task workloads, but would love to have large documents, if there's an public ones you can thinking of I'd like to know!
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.
> 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.
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.
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 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.
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.
I absolutely understand what you're saying. It makes complete sense. But I will never, ever shake the sense that software that isn't as fast as possible is offensive, immoral, delinquent -- the result of sloth, lassitude, lack of imagination, and a general hostility toward our noble Art.
"Fast enough" will always bug me. "Still ahead of network latency" will always sound like the dog ate your homework. I understand the perils of premature optimization, but not a refusal to optimize.
forgive me my rant, but when I see "just install it with cargo" I immediately lose interest. How many GB do I have to install just to test a little tool? sorry, not gonna do that
Having the equivalent jq expression in these examples might help to compare expressiveness, and it might help me see if jq could “just” use a DFA when a (sub)query admits one. grep, ripgrep, etc change algorithms based on the query and that makes the speed improvements automatic.
Some bits of the site are hard to read "takes a query and a JSON input" query is in white and the background of the site is very light which makes it hard to read.
I am excited for some alternative syntax to jq's. I haven't given much thought to how I'd write a new JSON query syntax if I were writing things from scratch, but I personally never found the jq syntax intuitive. Perhaps I haven't given it enough effort to learn properly.
Many Useless Uses of cat in this documentation. You never need to do `cat file | foo`, you can just do `<file foo`. cat is for concatenating inputs, you never need it for a single input.
Since the query compilation needs exponential time, I wonder how large the queries can be before jsongrep becomes slower than all the other tools. In that regard, I think the library could benefit from some functionality for query compilation at compile-time.
88 comments
[ 9.5 ms ] story [ 130 ms ] thread- Someone likes tool X
- Figures, that they can vibe code alternative
- They take Rust for performance or FAVORITE_LANG for credentials
- Claude implements small subset of features
- Benchmark subset
- Claim win, profit on showcase
Note: this particular project doesn't have many visible tells, but there's pattern of overdocumentation (17% comment-to-code ratio, >1000 words in README, Claude-like comment patterns), so it might be a guided process.
I still think that the project follows the "subset is faster than set" trend.
Sometimes those will actually need to process through a bunch of data unexpectedly.
Sometimes those will be run on a loop - once per second, N per minute (etc), and the results will be used to monitor a situation until a bug is fixed or a spike in load is resolved or a proper monitoring program/metric can be deployed.
Sometimes those are to investigate a pegged CPU and the amortized lower runtime across all the tasks on the CPU is noticable.
We run our machines hot and part of the reason we can do that is being in the habit of choosing lower cost (in cycles) tooling whenever we can. If i can spend a little time and effort learning a tool that saves a bunch of cpu in aggregate, its a win. When the whole company does it, we can spend a lot less on hardware than it costs in engineer time to make these decisions.
Another way of putting it is: its a type of frugality (not cheapness, just spending wisely). If you save a dollar once, its nothing. If you have a habit of saving a dollar every time the opportunity arises, it adds up quickly. By having a habit of choosing more performant tools, you're less likely to hit a case where you wish you did use more performant tools, and are practiced at it when the need arises for pure parsimony and it's less painful.
Had to spend some efforts to set up completions, also there some small rough edges around commands discoverability, but anyway, much better than the previous oh-my-zsh setup
Ideally, wish it also had a flag to enforce users to write type annotations + compiling scripts as static binaries + a TUI library, and then I'd seriously consider it for writing small apps, but I like and appreciate it in the current state already
https://news.ycombinator.com/item?id=47542182
The reason I was interested, was adding the new tool to arkade (similar to Brew, but more developer/devops focused - downloads binaries)
The agent found no Arm binaries.. and it seemed like an odd miss for a core tool
https://x.com/alexellisuk/status/2037514629409112346?s=20
> Jq is a powerful tool, but its imperative filter syntax can be verbose for common path-matching tasks. jsongrep is declarative: you describe the shape of the paths you want, and the engine finds them.
IMO, this isn't a common use case. The comparison here is essentially like Java vs Python. Jq is perfectly fine for quick peeking. If you actually need better performance, there are always faster ways to parse JSON than using a CLI.
[0]: https://github.com/micahkepe/jsongrep
However, as someone who always loved faster software and being an optimisation nerd, hat's off!
netstrings has no such issues
Second, some comments on the presentation: the horizontal violin graphs are nice, but all tools have the same colours, and so it's just hard to even spot where jsongrep is. I'd recommend grouping by tool and colour coding it. Besides, jq itself isn't in the graphs at all (but the title of the post made me think it would be!).
Last, xLarge is a 190MiB file. I was surprised by that. It seems too low for xLarge. I daily check 400MiB json documents, and sometimes GiB ones.
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.
>
> 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.
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.
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.
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
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
"Fast enough" will always bug me. "Still ahead of network latency" will always sound like the dog ate your homework. I understand the perils of premature optimization, but not a refusal to optimize.
And I doubt I'm alone.
It does some kind of stack forking which is what allows its funky syntax
Some bits of the site are hard to read "takes a query and a JSON input" query is in white and the background of the site is very light which makes it hard to read.
The whole tool would be like a few dozen lines of c++ and most likely be faster than this.