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Julia 1.6 addresses latency issues

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Re: Julia 1.6 addresses latency issues

#61

Post by neolog »

krastanov wrote: post #11
up6w6 wrote: post #9

I use and love Julia but I really wanted to see the general purpose language that is claimed. On one hand, you see amazing scientific libs like DifferentialEquations.jl, on the other side, things like the PackageCompiler.jl mentioned just sucks at generating binaries for daily basis.

Isn't "generating binaries" just as bad for other interpreted (interpeted-ish) languages? If you generate a "python binary", you need to package python with your binary. Same for perl/ruby. It just seems weird that people expect julia to be able to do that. It is cute that PackageCompiler.jl exists and it is cute that more AOT compilation work is being currently done, but it seems crazy to expect Julia to be good at…

> Isn't "generating binaries" just as bad for other interpreted (interpeted-ish) languages?

Python is famously bad at this. I hope Julia's proponents don't stop at "look we're only as bad as Python".

Re: Julia 1.6 addresses latency issues

#62

Post by neolog »

hpcjoe wrote: post #53
up6w6 wrote: post #31

Earlier quoted context omitted.

> And by extension, it seems weird to me to complain that Julia is not a general purpose language because it can not generate binaries. What stops me from making the same statement about python, which is definitely general purpose? I agree that generating binaries don't make a language general purpose, I just tried to give an exemple of an ad hoc non scientific thing that is considered "important" to the community (i…

A non-scientific thing I've been doing for the last few months at the day job, with Julia. 1) querying a time series database of systems metrics at scale for (large) fleets. This is being done via a JSON API. Directly in Julia. 2) Creating data frames from these queries, and performing fleet wide analytics. Quickly. Millions to hundreds of millions of rows in the data frames, typically 4-20 columns. Directly in Julia…

What's a fleet in this case?

Re: Julia 1.6 addresses latency issues

#63

Post by orbots »

krastanov wrote: post #59
orbots wrote: post #57

Earlier quoted context omitted.

Julia claims to "solve the two language problem". i.e. prototype in python, rewrite in c++. The two language problem is not solved with Julia if you can't effectively generate binaries.

I have never really heard the name "two language problem" to refer to what you are describing. Whenever I have heard these words it has referred to "I want a high-productivity newbie-friendly introspective language like python, but I do not want to write C modules when I need fast inner loops". Julia seems to solve this already, without providing compact binaries. A sibling comment made a point about "compiling down…

Right. It used to be referenced on the front page of julialang.org Seems they don't really use that in the sale pitch anymore. Maybe that proves my point. It's easy to find references to julia claiming to solve the two-language problem though. I am someone who this two-language problem they speak of addresses.

I love Julia. Which is why it's so painful that I have to rewrite all my elegant Julia prototype code in C++, so I can compile into a shared lib for the users. Every. Single. Time. Two languages.

Now that it isn't the main front and centre claim, I feel a bit less bitter about using it as a prototyping language.

Waiting another 5 years and maybe it really will solve the two-language problem.

Re: Julia 1.6 addresses latency issues

#64

Post by jampekka »

smabie wrote: post #51

So I used to be a big proponent of Julia, and in some ways, I still am. But I very recently tried to write a high performance production system in it, and was sorely disappointed. The tooling is just so buggy and it's clear that the community isn't really interested in using it for anything besides modeling/research in a Jupyter notebook. Things that kind of suck about using Julia for production: 1. Never could get R…

It's sad to see that the Julia ecosystem does not address these issues at all. Maybe Julia people are in some kind of bubble of people who like Julia and generalize that to all potential users and contributors. The true process is probably that people with other workflows (eg. non-REPL/Notebook) and past experiences (esp. more "general purpose" languages) just give up and are never heard of again.

I've ranted about very similar things for some time now, and had some fruitful discussions, and I even offered to help to try to scratch some of the itches me and others are suffering from. I've now mostly given up too.

It's a bit sad for me. I think Julia has many things right and the core concepts are potentially revolutionary. But for me it seems that Julia ecosystem is a bit too jealous of their discovery to let it free. Weird.

Re: Julia 1.6 addresses latency issues

#65

Post by kruxigt »

Tainnor wrote: post #60
smabie wrote: post #51

So I used to be a big proponent of Julia, and in some ways, I still am. But I very recently tried to write a high performance production system in it, and was sorely disappointed. The tooling is just so buggy and it's clear that the community isn't really interested in using it for anything besides modeling/research in a Jupyter notebook. Things that kind of suck about using Julia for production: 1. Never could get R…

I would also add: 5. The module system is very primitive. 6. The testing framework is extremely barebones. I agree with your assessment, Julia is great for crunching numbers etc., but I wouldn't write a whole application in it.

I agree with you guys. I have been coding in Julia for 2 years and very little has happened in tooling. For example, the graphical profiler is buggy. I love the language though. Hoping things will change!

Re: Julia 1.6 addresses latency issues

#66

Post by jampekka »

jampekka wrote: post #64
smabie wrote: post #51

So I used to be a big proponent of Julia, and in some ways, I still am. But I very recently tried to write a high performance production system in it, and was sorely disappointed. The tooling is just so buggy and it's clear that the community isn't really interested in using it for anything besides modeling/research in a Jupyter notebook. Things that kind of suck about using Julia for production: 1. Never could get R…

It's sad to see that the Julia ecosystem does not address these issues at all. Maybe Julia people are in some kind of bubble of people who like Julia and generalize that to all potential users and contributors. The true process is probably that people with other workflows (eg. non-REPL/Notebook) and past experiences (esp. more "general purpose" languages) just give up and are never heard of again. I've ranted about v…

Actually not probably that weird. May be a sort of impedance mismatch between academia and software scenes. It's very common in academic circles to be quite jealous of ideas, especially good ones. The academic game is often to get your name associated with some good idea, and this is what carries a researcher in their career. I find this rather counterproductive and try to avoid it myself.

I'm a researcher but I have a background in software development, and especially open source. Academia is way behind software in openness, which is rather bizarre as the institutional role of academia is usually seen as providing new ideas and challenging old thinking so the community can prosper. There's some kind of a bug in the current academic culture that causes it to freeze up when it should fulfill its promise to share its findings with the world.

Probably a good way to debug this thing is to follow the money and why on earth do we have these weird hats and robes?

Re: Julia 1.6 addresses latency issues

#67

Post by tarlinian »

orbots wrote: post #63
krastanov wrote: post #59

Earlier quoted context omitted.

I have never really heard the name "two language problem" to refer to what you are describing. Whenever I have heard these words it has referred to "I want a high-productivity newbie-friendly introspective language like python, but I do not want to write C modules when I need fast inner loops". Julia seems to solve this already, without providing compact binaries. A sibling comment made a point about "compiling down…

Right. It used to be referenced on the front page of julialang.org Seems they don't really use that in the sale pitch anymore. Maybe that proves my point. It's easy to find references to julia claiming to solve the two-language problem though. I am someone who this two-language problem they speak of addresses. I love Julia. Which is why it's so painful that I have to rewrite all my elegant Julia prototype code in C++…

It could only solve the two language problem if the "users" were writing their program in Julia themselves. Otherwise your ideal solution is still using two languages. And if they are writing their program in Julia, there's no reason to compile your code into a shared library; you'd just share a Julia package with them.

Re: Julia 1.6 addresses latency issues

#68

Post by cbkeller »

orbots wrote: post #63
krastanov wrote: post #59

Earlier quoted context omitted.

I have never really heard the name "two language problem" to refer to what you are describing. Whenever I have heard these words it has referred to "I want a high-productivity newbie-friendly introspective language like python, but I do not want to write C modules when I need fast inner loops". Julia seems to solve this already, without providing compact binaries. A sibling comment made a point about "compiling down…

Right. It used to be referenced on the front page of julialang.org Seems they don't really use that in the sale pitch anymore. Maybe that proves my point. It's easy to find references to julia claiming to solve the two-language problem though. I am someone who this two-language problem they speak of addresses. I love Julia. Which is why it's so painful that I have to rewrite all my elegant Julia prototype code in C++…

I think the main reason they stopped referencing that claim is that "two-language problem" means too many different things to different people. But yes, real static compilation would be great.

Re: Julia 1.6 addresses latency issues

#69

Post by vindarel »

krastanov wrote: post #11
up6w6 wrote: post #9

I use and love Julia but I really wanted to see the general purpose language that is claimed. On one hand, you see amazing scientific libs like DifferentialEquations.jl, on the other side, things like the PackageCompiler.jl mentioned just sucks at generating binaries for daily basis.

Isn't "generating binaries" just as bad for other interpreted (interpeted-ish) languages? If you generate a "python binary", you need to package python with your binary. Same for perl/ruby. It just seems weird that people expect julia to be able to do that. It is cute that PackageCompiler.jl exists and it is cute that more AOT compilation work is being currently done, but it seems crazy to expect Julia to be good at…

> Isn't "generating binaries" just as bad for other interpreted (interpeted-ish) languages?

I might have a counter example: Common Lisp (a compiled language) can be run from sources as a script (like interpreted-ish languages) and we can build self-contained binaries. With SBCL they weight ±20MB minimum (proprietary implementations do tree shaking) and they start instantly.

Re: Julia 1.6 addresses latency issues

#70

Post by orbots »

jampekka wrote: post #64
smabie wrote: post #51

So I used to be a big proponent of Julia, and in some ways, I still am. But I very recently tried to write a high performance production system in it, and was sorely disappointed. The tooling is just so buggy and it's clear that the community isn't really interested in using it for anything besides modeling/research in a Jupyter notebook. Things that kind of suck about using Julia for production: 1. Never could get R…

It's sad to see that the Julia ecosystem does not address these issues at all. Maybe Julia people are in some kind of bubble of people who like Julia and generalize that to all potential users and contributors. The true process is probably that people with other workflows (eg. non-REPL/Notebook) and past experiences (esp. more "general purpose" languages) just give up and are never heard of again. I've ranted about v…

I'm a Julia user who has also given up as a Julia community member. The bubble is real. I found too often when I wanted to do something outside of that bubble and asked for help, I got unhelpful advice which amounted to "why do you want do something outside of our bubble?"
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