Storm 2.0
storm.apache.org
storm.apache.org
While Storm's Clojure implementation served it well for many years, it was often cited as a barrier for entry to new contributors. Storm's codebase is now more accessible to developers who don't want to learn Clojure in order to contribute.
Very common story that I hear from a lot of shops that tried to go Clojure first. Great language, but too little penetration amongst developers. Makes it very difficult to effectively recruit employees/contributors.
At some point, you just accept that it's more important to get a new warm body than to continue pursuing some idealized programming perfection.
> The new Java-based implementation has improved performance significantly, and made Storm's internal APIs more maintainable and extensible.
The new Java-based implementation has improved performance significantly, and made Storm's internal APIs more maintainable and extensible.
It's not totally clear if this is because it's been rewritten Java, but the intrinsic qualities of the language do matter; there are real tradeoffs between maintainability and dynamism/flexibility. I feel like this sometimes gets shortchanged in these narratives.
> Storm 2.0.0 introduces a new core featuring a leaner threading model, a blazing fast messaging subsystem and a lightweight back pressure model. It is designed to push boundaries on throughput, latency and energy consumption while maintaining backward compatibility. The design was motivated by the observation that existing hardware remains capable of much more than what the best streaming engines can deliver. Storm 2.0 is the first streaming engine to break the 1 microsecond latency barrier.
I have noticed this with every "X produces code faster than C": you begin with two programs that use a suboptimal algorithm, then you take your non-c language and try to write C in it. The result is always awful and removes most reasons not to use C in the first place.
This has somewhat changed with rust and in some sense C++,but for other languages my point still stands. They have a nice idiomatic golden path that is fast enough for most cases. Once you need performance badly enough you have to treat you language as an assembler, and then you will always lose to languages that actually are good at that.
I say this as a scheme/Haskell weenie. Writing really performance scheme and Haskell code often means writing ugly code.
.NET Native, D, Delphi, Ada and Eiffel also have pretty fast compilers, while offering quite powerful languages.
Lets even pick Turbo Pascal 7.0 for MS-DOS, which was quite feature rich, and was able to compile very large programs in a couple of seconds.
Also Visual C++ with modules preview support, incremental compilation and linking is also reasonably faster than the FOSS alternatives.
It is only a matter how much money one is willing to invest into improving tooling support.
There is no reason compiling things should not compile at similar speeds to chez unless you are telling your compiler to ootimise everything.
C++/ruae are just exceptionally slow and it became the new bottom line somehow. I know rust does a lot of housekeeping, but after using chez and sbcl, 45s for a 1.5kloc project is killing me inside.
The same with Clojure, suddenly you start writing Java with parenthesis.
In the JVM, if you want absolute control over performance its better to just write Java for those parts (don't know much about Kotlin).
Surely what they mean is they've rewritten it to be faster, and switched to Java at the same time because they want to open up the contributor pool.
And as a sibling comment mentions, the announcement does clearly state that a rather extensive rewrite was done, including switching to a new architecture, with likely performance improvements coming from that - it's nowhere close to a pure Java vs. Clojure comparison.
Since you can argue knowledge of a language does help with maintenance and extensibility. With this, it also makes more sense for the following bit about finding people able to contribute. No contributors is pretty bad for maintenance.
At my work, we use Clojure, but I do often wonder what would happen if the current Clojure devs left. New devs unfamiliar with Lisps, FP, and Clojure would most likely have a hard time maintaining the code base and extending it, and if they try to rush it before really learning the language, would quickly degrade the quality of the code base, compounding the effect.
I think as long as you continue to have one strong Clojure dev on the projects, you'll be fine, as they can direct newcomers and help them transition to Clojure, but if you lost that, I think a rewrite in a different language would make sense, or there's a risk of the code base degrading quite quickly.
I don't understand why it would be a challenge to pick up Clojure.
Furthermore, I think it also has to do with the order in which these courses are taught. When I did a small introduction to FP at my university, a lot of people who had no prior experience in programming picked up Haskell much more easily than those who already had a background in imperative/OO programming.
(Though that strengthens the point - FP is often quite a leap for programmers who have used imperative languages for a long time.)
Debugging in FP feels different to most people, where our thoughts is tuned to the procedural model with observing states and form our hypothesis from there.
Another disadvantage with niche programming language is not enough Stack Overflow help there. That alone will drive most people away.
Another view of this would be: progress in this industry is made by those who succeed while sticking to their guns and not optimizing their infrastructure for the available worker pool.
Could there be other reasons? Maybe they rushed?
This is in the context of software development in general, not this specific project per se.
There's no reality here, just myth. That switching to Java would drive quality up makes at least as much sense as it driving it down.
If you're referring to the particular languages, then the reality is that no big effect has been found for the choice of programming language on software quality. As lack of evidence in favor of a big effect is evidence of its lack, the most probable explanation is that no such effect exists (it's possible a small effect exists, but we don't know in which language's favor). And, indeed, while there is a theory explaining (and even predicting ahead of time) why there is no big effect to the choice of the programming language, not only is there no empirical evidence suggesting there is such an effect, there is no theory to predict it, either. That language has a big effect on quality is, at this point, no more than wishful thinking among a minority of developers who are big programming language fans. It's a bedtime story. (I am not saying that language didn't ever have a big effect or that it never will, just that both theory and observation show that there isn't one currently among "reasonable" languages in common use; also, I have used and I like both Java and Clojure)
And if you're only referring to the priority of making the project more accessible, then I don't understand your comment at all. There are many, many more experienced Java developers than experienced Clojure developers, and experienced developers are at least as likely not to bother learning a new language in order to contribute to a project (although perhaps for different reasons). Picking a popular language makes the project more accessible to experienced developers.
What has been shown to drive quality up or down is process. If you have a good process, then making the project more accessible can help, and if you don't then you're screwed anyway.
Do you mean "defect rate" or something else?
Substantiate that. I say it's garbage.
<https://www.cse.iitk.ac.in/users/karkare/courses/2010/cs653/..., and this BTW is from 1994 so this evidence has been around for ages
Language LOC Documentation Lines Dev time (hours)
(1)Haskell 85 465 10
(2)Ada 767 714 23
(3)Ada9X 800 200 28
(4)C++ 1105 130 –
(5)Awk/Nawk 250 150 –
(6)Rapide 157 0 54
(7)Griffin 251 0 34
(8)Proteus 293 79 26
(9)RelationalLisp 274 12 3
(10)Haskell 156 112 8
comments of note:
(2) The Ada solution was written by a lead programmer at NSWC; in this sense it represents the “control” group. The developer initially reported a line count of only 249; this was the numberof lines of imperativestatements as reported by theSun Adacompiler, anddid notinclude declarations, all of which were essential for proper execution. The line count of 767 is based on the actual code in and does not include lines with only termination characters.
(4) TheC++solutionwaswrittenbyanONRprogrammanagerafterhavingfirstwrittentheAwk solution described in the next paragraph. In addition to these 1105 lines of code, the developer also wrote a 595-line “test harness.” No development times were reported [Note: C++ has evolved a lot since then, but perhaps so has haskell]
(10) Intermetrics, independently and without the knowledge of NSWC or Yale University, con-ductedan experimentof its own: theHaskell Report was given to anewly hiredcollege graduate, who was then given 8 days to learn Haskell. This new hire received no formal training, but was allowed to ask an experienced Haskell programmer questions as issues came up during the self study. After this training period, the new hire was handed the geo-server specification and asked to write aprototype in Haskell. Theresulting metrics shown in row 10 ofthe tableare perhaps the most stunning of the lot, suggesting the ease with which Haskell may be learned and effectively utilized.
Also mentioned was "The use of higher-order functions [in haskell] is noteworthy" so language features did help. Actual evidence.
> As lack of evidence in favor of a big effect is evidence of its lack
yeah right. Let me rephrase that for you - Lack of knowledge by an HN poster is not evidence of lack of evidence.
> What has been shown to drive quality up or down is process
Evidence please? My experience is that process can be rigorous but useless crap. My old boss said "process is not sufficient to produce quality, but it is a necessary"
There's plenty more in that PDF, please read it.
Evidence of what? This is not a study of software development at all, but of prototyping using a program with no more than a few hundred lines. I'm talking about effects on software development. The issue of prototyping/tiny programs is a completely separate one.
> Substantiate that
I don't know how I can substantiate the lack of evidence, but here's a recent failed attempt to find evidence: https://arxiv.org/pdf/1901.10220.pdf
> Lack of knowledge by an HN poster is not evidence of lack of evidence.
True. While I have been following the subject for at least the past 20 years (and I have read your PDF several times already, including shortly after it was published), it is certainly possible I have missed something. If there's any evidence of a large effect you believe you've found, let me know.
> Evidence please?
Sure. Here's code review, for example (I don't have time to discuss each paper -- as they're quite different -- but they all paint a similar picture). BTW, while programming language studies are debating effects in the 0-15% range, these report effects in the 30-80%:
* What We Have Learned About Fighting Defects, 2002 -- https://www.cs.umd.edu/~mvz/pub/eworkshop02.pdf
* The Impact of Design and Code Reviews on Software Quality: An Empirical Study Based on PSP Data, 2009 -- https://www.pitt.edu/~ckemerer/PSP_Data.pdf
* Large-Scale Analysis of Modern Code Review Practices and Software Security in Open Source Software, 2017 -- https://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-...
* What Types of Defects Are Really Discovered in Code Reviews?, 2003 -- https://ieeexplore.ieee.org/document/4604671
* Modern Code Reviews in Open-Source Projects: Which Problems Do They Fix?, 2014 -- https://www.testroots.org/assets/papers/2014_beller_bacchell...
* The impact of code review coverage and code review participation on software quality: a case study of the qt, VTK, and ITK projects, 2014 -- https://dl.acm.org/citation.cfm?id=2597076
* Best Kept Secrets of Peer Code Review, 2013 -- https://smartbear.com/SmartBear/media/pdfs/Best-Kept-Secrets...
* Modern Code Review: A Case Study at Google, 2018 -- https://storage.googleapis.com/pub-tools-public-publication-...
If we summarize our current state of knowledge (not myth) it is this: process matters a lot; language matters little, if at all (with all the caveats I mentioned in other comments, such as diminishing returns etc.).
> then the reality is that no big effect has been found for the choice of programming language on software quality
Then I show some evidence giving small programs rapidly developed, which you then say doesn't count because it's 'tiny' and 'prototyping'. You also don't define quality which gives you lots of wriggle room.
Nope, 1000 line programs aren't tiny. They aren't industry monsters but you can't dismiss them because it contradicts you. It's not proof, but it is strong evidence.
...arxiv paper... Interesting, thanks. It would have been helpful to have posted that in your original post.
However from <https://soarsmu.github.io/papers/A_Large_Scale_Study_of_Mult..., and note this paper is not mentioned, as in not debunked, in the above arxiv paper.
"Bhattacharya et al. study four open-source projects which use C and C++, i.e., Firefox, Blender, VLC Media Player and MySQL to understand the impact of languages on software quality [20]. They compute several statistical measures while controlling for factors, such as developer competence and software process. They find that applications previously written in C are migrating to C++ and C++ code is often of higher quality, less prone to bugs, and easier to maintain than C code."
and from that same paper:
"As can be seen in Tables 8, 9, and 10, the mean de- fect density values for the C sets can be up to an order of magnitude higher than the mean values for the C++ sets."
> Sure. Here's code review...
I was talking about your claim about languages not mattering, I did not mention code review. All these papers are about code review. This is relevant to my code review comment (edit: I meant process comment), they don't say anything about language vs bugs (unless you wish to point out a paper that does).
> process matters a lot
And I agreed with you, I just said it didn't deliver quality, it just prepared the ground for it. With enough process you can close any hole in a language, but it gets exponentially expensive.
Only if you insist on uncharitable reading. I'm talking about software development; if I mistakenly assumed that could be left implicit, I'm sorry. And ~500 line programs are positively minuscule. JQuery is ~50KLOC, and an average business system is ~5MLOC. We're talking four orders of magnitude between those prototypes and a rather average industry system size (systems commonly run to tens and even more than 100 MLOC).
> It's not proof, but it is strong evidence.
I don't think it matters if it's strong or weak evidence, as it's not even about software development.
> the C sets can be up to an order of magnitude higher than the mean values for the C++ sets.
As I mentioned in another comment, C is not a good example. It's a ~50-year-old language, and the theory that correctly predicted that languages won't make a big difference was based on diminishing returns. I.e. not that no two languages have ever been or could ever have a big difference, but that over time the ability to affect quality with language would severely diminish. The original prediction of that theory was that no 10x improvement would be made by a single language improvement over a decade, and was called overly pessimistic by PL fans. It's not been over thirty years, and we have doubtfully made a 3x boost with all language features combined.
If you want a more precise statement: no theory or empirical evidence supports the claim that a reasonable choice among production languages developed in the past three decades or so has a big impact on any measurable bottom-line metric.
> I just said it didn't deliver quality
But those papers show that, unlike language, process does have a big impact on quality.
> With enough process you can close any hole in a language, but it gets exponentially expensive.
You are now making an unsubstantiated claim that contradicts a substantiated claim. Programming languages (with the caveats above) have not been found to have a big effect (nor is there a theory that suggests they do), while process has.
And the value different languages may add is entirely about software development.
> I don't think it matters if it's strong or weak evidence, as it's not even about software development.
Programming languages are not about software development? Oh do go on.
> As I mentioned in another comment, C is not a good example.
A study of C vs C++ strongly indicates your claim about languages is false and suddenly C is not a good example? I'm trying to believe I'm just misunderstanding you but it's getting more difficult.
> The original prediction of that theory was that no 10x improvement would be made by a single language improvement
This isn't what you said. Let me remind you "If you're referring to the particular languages, then the reality is that no big effect has been found for the choice of programming language on software quality"
The goalposts aren't being moved, you've just bought them plane tickets to barbados.
> If you want a more precise statement: no theory or empirical evidence supports the claim that a reasonable choice among production languages developed in the past three decades or so has a big impact on any measurable bottom-line metric
Another claim. Show me the study that says that.
> But those papers show that, unlike language, process does have a big impact on quality.
It can if done properly; it does not do so automatically. You can have code reviews that are of little use because you have no spec to review the code against. I have been in that very position. I don't dispute the value of process but it's a necessary but not sufficient condition to bring about quality. I also agree code reviews are good, if done properly.
ME >> With enough process you can close any hole in a language, but it gets exponentially expensive.
YOU > You are now making an unsubstantiated claim that contradicts a substantiated claim.
If I use C I have to worry about garbage leaks, double-freeing pointers, out-of-bounds accesses etc that can be detected with code reviews. If I use python, I never have any of these problems so a code review need not check for these. That's a lot cheaper.
(Edit: weird stuff happening to my post, may appear twice)
I can't repeat all the caveats every time I say something. I assume readers believe my comments are at least reasonable, even if they disagree with them. For convenience, I restated the current state of knowledge more precisely in my previous comment. If you're interested in what I have to say, assume I'm not an idiot, and perhaps we could have an interesting discussion, and if you think I'm an idiot, then there's no point in arguing at all.
> Show me the study that says that.
Show me the study that says otherwise. I don't need to provide evidence for the lack of an effect (although I did). The lack of an effect is, at the very least, the default hypothesis in this case (as in many others) as there is no theory suggesting we should believe otherwise (while a theory that explains why languages increasingly have smaller effects has made correct predictions).
> It can if done properly
That's your hypothesis. We've been trying to find evidence of that, or others like it, for a long time -- both in academia and in industry -- without success. We simply do not observe that the choice of language today (among reasonable ones etc.) has a big effect, either in studies or in industry practice. But if you've found a language that can drastically reduce software development costs and/or increase quality at scale, that discovery can be easily translated to billions of dollars. Go ahead and make them.
"In terms of programming-in-the-large, at Google and elsewhere, I think that language choice is not as important as all the other choices: if you have the right overall architecture, the right team of programmers, the right development process that allows for rapid development with continuous improvement, then many languages will work for you; if you don't have those things you're in trouble regardless of your language choice."
I have a strong suspicion that people smart enough to do advanced meta programming on their own are not smart enough to collaborate with equally skilled coworkers on code that uses all those abstractions to the max. Even collaborating with your own former self is more difficult that writing new code.
So I think _some_ dumbing down is inevitable. The question is how that can be enforced. Choosing a dumber language to bludgeon everyone into submission is the nuclear option so to speak.
I often think of this Dijkstra quote about abstraction: "The purpose of abstraction is not to be vague, but to create a new semantic level in which one can be absolutely precise".
But I think there's something missing in this thought. Abstraction, especially when its precise, is also a form of compression. To understand what a particular abstract expression means in a concrete case requires decompression, which may require a lot of mental effort.
These are admittedly extremely half-baked thoughts...
[1]: Once a certain point has been reached; theory does predict diminishing returns.
Do you mind sharing a source for this? It seems trivial to generate a programming language (Brainf*ck) that performs very poorly.
A more likely statement: all commonly used languages are more or less on par.
I have read quite a few studies, and I always come away thinking that the methods used are inadequate to support any conclusions at all.
But does that mean there is no causal effect of programming language choice? I don't know and I'm not making any claims either way.
I was talking about abstraction in one person's mind vs abstraction shared between a group a people. And what I said could actually be the reason why the choice of programming language has little effect (if that is the case)
I'm also not making definitive claims, but we can't ignore observations, either. While small effects can appear or disappear depending on methodology, big effects are easy to find and hard to hide, especially in an environment with strong selection pressures. Therefore, the most likely explanation to why no big effect has been detected -- either in studies or in industry -- is that there isn't one, and that should at least be enough to make it the working hypothesis. So before explaining effects that have yet to be detected we should establish that they exist at all, something we have so far failed to do.
There may well be a small effect, and there could still be a large effect, although the chance of that is small unless we have a really good explanation to why we haven't found it.
1) It is inconsistent with the personal experience of most developers. Few would claim that C is just as productive and safe as some garbage collected language (provided that both are suitable for the task at hand), or that a SQL group by statement is not more productive to write than the equivalent procedural code.
2) The methods used to study the subject are completely unfit for purpose.
3) It is inconsistent with the few results that seem at least somewhat well supported because they are simple enough to measure, such as the constant bug count per line of code.
I disagree. I've been programming for about 30 years now, and most reports I've received -- both from programmers and managers -- are that language doesn't matter; certainly not much. Carefully selected personal "feeling" report are worthless (especially in biased forums), as that would produce even more evidence that homeopathy is effective than that programming languages make a difference.
> Few would claim that C is just as productive and safe as some garbage collected language
I agree, but that's where the many caveats come in. First, my argument is more one of diminishing returns (following Brooks's theory). I.e., languages make an increasingly small difference. C may have been a big improvement over assemby, and Java may have been a smaller but still quite big improvement over C, but now differences are quite small.
Indeed, the effect of GC and memory safety vs C was one that was almost immediately detected by industry (once mature, performant, etc.) and triggered a huge shift. We do not see such shifts now. Companies move among mainstream languages, among non-mainstream languages, and between the two classes in a way that does not suggest a big effect at all.
> or that a SQL group by statement is not more productive to write than the equivalent procedural code.
That's a completely different matter. I don't think anyone believes that writing a 1MLOC program in SQL is easier than writing a similar one in Java or Python, even if the Python/Java one is 1MLOC, and the SQL one is 200KLOC. When the program is small, there can be large differences, but that's a completely different problem (and also explained by theory).
> The methods used to study the subject are completely unfit for purpose.
I disagree, but it doesn't matter. Big effects are easy to find and hard to hide. And in an environment with strong selective pressures, they're found even when no studies at all are conducted.
> It is inconsistent with the few results that seem at least somewhat well supported because they are simple enough to measure, such as the constant bug count per line of code.
It is not. First, the difference in LOC is not as big as PL fans claim (it can be big for small programs, not large ones). Second, you may want to review those results.
I don't necessarily disagree, but I'm a bit skeptical about the way in which you use the concept of diminishing returns. If I'm not mistaken then Brooks used diminishing returns in relation to headcount. And this is in fact how economists use the term as well - adding quantitatively more of one production factor.
But that doesn't apply to qualitative changes like introducing new production methods and tools, which is what programming languages are. New programming languages are not simply "more programming language".
If we agree that there have been observable effects of new programming languages in the past, then we cannot exclude the possibility of the same happening in the future.
>First, the difference in LOC is not as big as PL fans claim
What PL fans claim is a bit of a fluffy benchmark, but there are undoubtedly significant differences in LOC, certainly significant enough to make an economic difference.
>I've been programming for about 30 years now...
Shockingly, me too :)
Oh, I'm referring to "No Silver Bullet" and diminishing returns in the sense that languages at best help with "accidental complexity", so the less of it there is, the less languages can help.
> New programming languages are not simply "more programming language".
But there are inflexible theoretical limitations on their utility (even without Brooks). We know the effect of different programming constructs on expressive compression and reasoning costs. The closer we get to the limit, the less benefit we can have.
> then we cannot exclude the possibility of the same happening in the future.
I'm mostly pointing out that it's not happening at present. I'm less sanguine about future advances because of various limitations (and, BTW, Brooks's predictions were called overly pessimistic by PL fans at the time and it turned out they were too optimistic), but I won't rule out another major breakthrough, or possibly two.
> but there are undoubtedly significant differences in LOC, certainly significant enough to make an economic difference.
I don't think I agree with your first assertion (although that depends on what we mean by "significant" here), and I certainly disagree with your second. We simply have not been able to detect or induce such an effect. Here, too, there are theoretical results showing that increased expressiveness cannot lead to cheaper reasoning, which is not an obvious result even in the worst case (because there are far fewer "compressible" programs than non compressible ones).
>Here, too, there are theoretical results showing that increased expressiveness cannot lead to cheaper reasoning, which is not an obvious result even in the worst case (because there are far fewer "compressible" programs than non compressible ones).
I find that very interesting. Do you have a source for it?
* http://www.lsv.fr/Publis/PAPERS/PDF/Sch-aiml02.pdf
* http://www.lsv.fr/Publis/PAPERS/PDF/DLS-jcss-param.pdf
* https://www.cis.upenn.edu/~alur/Zohar03.pdf
What's important to put those results in context for those who are not familiar with the subject is that, in the context of complexity theory, the "model checking problem" does not refer to the complexity of a particular model checker algorithm, but to the inherent complexity of the problem of deciding whether a program M satisfies some property 𝜑 (i.e. whether M is a model of 𝜑 in the formal logic sense). The "model checking problem" is the closest to a mathematical description of what we usually mean when we talk of "reasoning about a program."
I've summarized these results and more here: https://pron.github.io/posts/correctness-and-complexity
Consider JVM and Java: that you can write Java seemingly without any knowledge about JVM is an illusion - you already learned a lot about how things like JVM work under the hood when first learning programming[0]. Learning more about JVM itself lets you write more efficient code and debug better.
Consider functions: it's near-impossible to contain all the information necessary to use a non-trivial function in its header[1]. That's why good code contains comments and other forms of documentation describing the abstraction in more details. Even then, it's not always enough - sometimes it's really much easier to understand what you need by reading the source[2].
Consider any appliance - be it a car, or a radio, or a dishwasher. You can use it to it interface, to some extent at least. But knowing what's going on under the literal hood really does help with use, and especially helps when something goes wrong. If you don't know what's hidden under the abstraction layer, any failure will likely be incomprehensible to you and leave you helpless.
--
[0] - In theory, it might be possible to learn some programming without learning anything about hardware or hardware-emulating abstractions. In reality, I've never seen it or heard of it, and I suspect that the simplest mental model of code execution is isomorphic to somewhat simplified computer or virtual machine.
[1] - Function name + name of its arguments + types of its arguments and return value, if available.
[2] - Then again, implementation code may not capture the entire abstraction either. That's why good code often features comments inside the implementation, explaining the rationale behind some of the less obvious code parts.
I think there's a misunderstanding. What I'm calling decompression has nothing to do with digging into the implementation of a particular abstraction. What I mean is merely tracking down all the indirections in the public interface and breaking them down to their concrete meaning in a specific case.
Some languages allow for a lot more moving parts than others. For instance, in Java obj.otherName means that otherName is an instance variable (or theoretically a class variable) and access time is guaranteed to be constant (tbd: caveats). It's not redefinable as it is in C#, Python or Swift. So there's one less thing to track down but also less flexibility.
Or take an extreme example like Go's range loop. It's defined only for a handful of builtin data structures. When you see a range loop, you know what it does without following any further indirections. It can be extremely annoying and create a lot of friction when you have to work with custom data structures. But it can make other people's code easier to read than in other languages.
Or take something like this:
a == b
So transforming an expression's possible meanings into its concrete meaning is what I call decompression. There may not be a need for looking anything other than public interfaces.
Also, you're talking about abstractions purely from the perspective of users. But we are often creators and maintainers of abstractions as well when we model a particular problem.
You might be interested in this book, Patterns of Software, which brings up the issue that inheritance in OOP isn't about reuse but about compression and how the implications of that are why it's not had that much success in following through on the "reuse" promise. http://dreamsongs.com/Files/PatternsOfSoftware.pdf
I'm an unabashed Clojure fanboy and will talk the language up to anyone who will listen, but one thing that I've been thinking about lately is that good judgment on abstraction use is necessary for using such powerful tools. I don't think the place to tackle it is by being "smart enough to understand," but rather by being "disciplined enough to not abstract sometimes." The exciting thing is that discipline doesn't require you to be super smart, just to think it's worth caring about.
Also half-baked, but I think it's something.
It's not that much harder to enforce than it is to enforce conventions in less powerful languages, and the convenience of working in a well-designed language is so nice.
On the more meta level it's weird what people expect devs to learn on the job or know up front. Companies expect employees to keep up with the latest nonsense in web dev, but can't pick up a new straightforward language? Unless maybe another Algol like Go or TypeScript? This Steve Yegge quote captures some of it:
"For some reason, programmers love to learn new stuff, as long as it's not syntax."
I can attest to this fact, as part of a unicorn upstart with dev offices in Sao Paulo and Berlin. Clojure onboarding has never been a major roadblock for new engineers. And we never hire asking for "X years of lang experience". Almost everyone in the (~300 strong) engineering team started with zero-to-little Clojure background.
(It's fine if your work sample test really just focuses on one language! But then make it part of the rubric if that's the answer you want, and tell the applicant about that rubric.)
I can see 1. being pretty easy to suss out (paid take home coding assignment is how I'd do it).
How do you assess 2.?
Also, we encourage our candidates to choose Clojure for their take-home assignment, even if they do not have any prior taste of it. This, for those of them who choose that option, gives an idea of if they would enjoy working in it. Our rubric however does not have a bias against developers who do not choose Clojure for their assignments, and we make this explicit to the candidates as well.
I think there are cultural reasons for that because enterprise treats devs like fungible cogs that you replace when they burn out. It tends to be highly dehumanizing environment where devs have no say, no autonomy, and no ownership. This naturally pushes out people who have options, and you end up with a pool of devs who just want any job that pays the bills.
Its mostly approach to any work in general. If it were upto them, these are really the kind of the people who would dig earth with spoons and shovels, instead of heavy machinery.
The idea is simple, should you use Spring + Java, you are likely to need say 60+ people to run a product well. It could take 15 to make it work in Clojure. But having 60 people has its own advantages from their perspective. Say 10 people decide to leave, they can hire 10 replacements for the lowest prices from the market, train them on the application and get it going. Eventually the whole team could leave and get replaced this way, reducing the problem to a bit like the Ship of Theseus paradox. But it works for them.
If they use Clojure, they have to treat people well, pay them well to retain them. Because there teams tend to be small and a exodus puts everything at risk.
They have to use spoons and shovels, personnel trained to work on heavy machinery are expensive, training is expensive and replacing them is expensive.
I'm a Software Engineer, and while I have my go-to tools, I'd like to think I make an informed choice to use what fits the task at hand .
An Engineer who's a comfortable polygot is perhaps also a better Engineer overall.
It is the usual "Jack of all trades, master of none." consulting, but it does come in handy when we need to deal with mixed stacks end-to-end.
For every one shop that looks at darling niche stuff and thinks, "Ooh, that probably makes him or her a better programmer", there's ten shops who look at it and think, "They're probably going to be insufferable to work with, undermine the architects at every turn, and spend their whole time complaining about the tools we use".
As an aside, if you see Spring as existing to correct issues with the underlying Java language, then I'm highly skeptical that you've ever had meaningful experience with either one. Spring is a portfolio of libraries, stretching across over a dozen business application development domains, with inversion of control as the only common thread. NO language has all that baked into its standard library, and you'd have to pull down a bajillion NPM packages (or whatever) to even come close to approximating it.
Let's please avoid personal attacks if at all possible. Spring started out with the dependency injection framework and "aspect-oriented programming". It was marketed as an alternative to EJB. Web frameworks and other add-ons came later. If you don't see DI and AspectJ as working around Java's weaknesses, then I encourage you to try a more expressive language.
In an expressive language (e.g. Clojure or Haskell), DI and AspectJ could be, for example, replaced by reifying a program as data and using modular interpreters. One interpreter using mock data, another talks to the database, uses transaction boundaries and logs. This sort of solution is unfortunately just not very practical in Java.
In another expressive language like Common Lisp, it has generic functions which 1) let you dispatch on more than just the class type of the first argument (implicitly in Java, explicitly 'self' in Python) which is a feature that by itself removes a lot of Java back-bending and 2) you can specify :before and :after and :around methods to provide the benefits of aspects with the built-in function compute-applicable-methods available to help see everything that might apply when invoking a method with specific arguments. There's also metaclasses which open other doors. There's just a whole lot of built-in expressiveness in the languages beyond the Java and JavaScript ecosystems.
I've been happily employed (and regularly solicited) as a Clojure developer for over 8 years.
There's no shortage of Clojure dev positions for developers that want to write Clojure.
Optimizing for new volunteer contributors goes beyond core language choice anyway. For an interesting description of how the game Battle for Wesnoth tried to do it, see: http://aosabook.org/en/wesnoth.html
Presumably people who consider contributing to the open source have some spare time and love programming. Wouldn't they find it exciting to contribute while also learning a cool new language?
And then, even if you wanted to learn something new, to a lot of people, it matters what that something is. Unless the person is really set on contributing to Storm specifically, then the barrier of Clojure is still significant. They may prefer to spend their new language learning bandwidth on something with more momentum.
And even if you have to hire devs who don't already know the language I really don't understand the difficulty in learning Lisp - few languages are simpler or easier to grok.
Some things I observed about the Clojure companies:
- Their HR seemed slower than the non-Clojure companies I was dealing with. I don't think this has anything to do with Clojure, but I am no longer working in Clojure full-time because the most credible offers took too long and I've found non-Clojure work I love.
- Outside of trading firms, I did the most whiteboard coding questions with Clojure firms compared to shops looking to hire for Python or Elixir. I like whiteboard work, so this was fine for me.
- 6 Clojure companies, 4 different conccurrent processing models and 6 different service frameworks. Neither of these is necessarily bad, but the community was much more fractured than I realized.
- Of the 6 Clojure orgs, 4 were actively hiring (had open roles) and 2 were passively hiring whenever someone materialized on IRC/Slack/Twitter. This leads me to think if you want a Clojure job, you should probably reach out to people you know inside Clojure orgs and, barring that, the HR people at these orgs directly. This isn't a Clojure-specific thing, but worth keeping in mind.
- 4 of 6 didn't seem to have dedicates DevOps, leading to them looking for candidates also familiar with deploying, monitoring, and debugging Linux hosts. I think I was given heavier weight at some orgs because of a background doing this type of work for Clojure stacks. Might be an angle worth looking into if you don't have production Clojure but you do have Linux and Java deployment/monitoring/debugging/tuning experience.
We also rarely hire devs who already know Clojure, and we typically just train on the job. It's really not hard to do when you already have people who know the language on the team. In fact, if somebody can't learn Clojure, I would question if they can learn to work on a large project in general. Dev practices, architecture, code styles, tooling, and so on tends to change quite a bit from company to company. The language is only small part of that.
In case of Storm, Apache commons is run by Java devs who have zero interest in learning Clojure. So, it's not surprising they would rewrite Storm in their preferred language.
Granted, these are two different products, and maybe the Clojure one is just more attractive to the right kind of person. Nevetheless, in terms of quality vs. quantity of applicants, Clojure has been massively winning.
Firstly: Clojure isn't actually a problem. We hired people who are highly junior (one who even refused to call themselves a developer) and taught them Clojure. It was fine. It is true that you need a strong dev lead to guide them through that, but honestly, if you don't have a strong dev lead your Python/Java project is screwed too.
Secondly: look at Storm's increased success at Java data processing sweatshop^H^H^H^H^H^Hconsultancies. Of course "can write Java" is what you're going to get if most of your business revolves around the lowest bidder.
and yet... almost every time I've come in to a project where developers got past those boundaries.... they inevitably recreated patterns/idioms from tech 1 in to tech 2, and make tech 2 horrifically bad, and made it even harder for anyone who actually knew tech 2 to come in to the project and help.
adding other languages is more than just 'get over it' - without guidance from experienced people who can understand good/efficient ways to model the problem domains unique to a business idiomatically in the new tech, you're very likely adding even more technical debt that you won't even know about for months/years. And... IME, the "let's use new stack X" are moved on to another project or company by the time the technical debt is apparent to everyone.
At some point, you have to sit down and do the work with the tools you have if you want to get anything done. If I were to get serious about programming, I would use C# or Go because I found them the most accessible after trying lots of languages. There's nothing wrong with finding a niche.
Not only that, but knowing multiple languages has a multiplicative effect, massively expanding how you think of programming in all the languages you know, even the stable standbys like C#.
I think that is why Kotlin and Typescript are doing so well generally, they build on top of already established bases offering good new things without throwing out everything else.
The trade off is they are constrained from how far they can diverge from their roots but on the flip side that is a strength as well.
I like both, they feel productive without feeling totally alien.
The new Java-based implementation has improved performance significantly, and made Storm's internal APIs more maintainable and extensible.
Describes my dating life pretty well.
Yes, it got redone in Java, but the fact is that Clojure took it from nothing to one of the world's premier frameworks for distributed computing - something that might have been impossible with the same resources if Java was its starting language. And because of the commonality of the underlying JVM, choosing Clojure allowed the functional approach with far less risk because the transition later was (I am assuming) much less risky and smoother.
Looking at it in that light, this would be a huge boon to people considering starting new projects in Clojure (or possibly other JVM languages): it proves if they succeed and get so popular that moving to Java is the right thing, it can be done.
- Clojure dev
I also consider this a success story for Clojure. It gives Clojure another usecase: a "production-ready prototype" language where the resulting "prototype" can last for eight years and benefit thousands of developers until it gets rewritten to something else when all the hard questions are answered, and most experimentation/wandering is over.
I am drawn to the idea of scalable languages or languages with zero friction for interop.
This thread on Pallene is interesting https://news.ycombinator.com/item?id=18038619
It’s quite a mature language so I’m not sure that bodes we’ll for its prospects this late in the game.
Begs the question, why not just write it in Java? Then at least its more likely to be a refactor down the road rather than a rewrite.
I think clojure ought to be a production ready language that scales well. That’s what it was designed to be. However lisp seems to dichotomise devs into those that get it and those that don’t and thus alienates many would be team members.
I think it speaks of something.
(Personally, I think the change is rather evidence of the primary drivers behind Storm development in 2019, and... that's not a good thing.)
I saw Clojure become popular long before it was ready for the limelight: it definitely wasn’t pragmatism driving it. It was a fetish for syntax and paradigm.
It is a success story for Clojure, but this move is a big negative feedback for the language. A team starting out on an open-source project will be mighty reluctant to start it with Clojure; because it might get rewritten not so much into the future. That is not good news for Clojure
As for switching to Java, that makes perfect sense to me if that is what the contributors prefer. If you're going to make a big rewrite, you might as well change the language to one you prefer when you have the opportunity.
As someone who spends 100% of dev time in Clojure, I'm quite happy to see this development. Dipping into Java isn't uncommon for optimizations in Clojure, so this is like someone taking the time to do a massive under-the-hood optimization from the point of view of a Clojure user. I doubt it changes the project's status much in the Clojure community. Perhaps it'll even see an uptake in use.
What it doesn't say much about is Java vs. Clojure in my opinion. Different contributors, with different amounts of pertinent knowledge, and years apart. I'm not sure how you would control for those variables in a comparison. It should be read more as, "we put in a heck of an effort to make this thing faster and more useful", and kudos for that.
> It gives Clojure another usecase: a "production-ready prototype" language where the resulting "prototype" can last for eight years [...] until it gets rewritten to something else when all the hard questions are answered, and most experimentation/wandering is over.
That general story, first heard from Paul Graham, about projects starting with Lisp and being successful that way, before eventually being rewritten, works for me.
I've been hoping at least a couple college startups would be inspired by this to use Racket initially, but if they have, I haven't heard of it. (I speculate that the current FAANG feeder emphasis among CS students hasn't helped. Who has time to play with a Lisp, when the now-all-important whiteboard interviews won't use it.)
> Obviously, much more people will be able to consider contributing when it's in Java.
If you have a company, and you want to hire Lisp people (whether it's Clojure, CL, or Scheme/Racket), I think you can probably hire people, because Lisp people like getting paid to use Lisp.
If you're looking for unpaid/volunteer contributions to an open source project, there's all sorts of things that affect that, and it's not unusual to get little-to-no contributions.
This is correct, it was “Storm ditches Clojure in favor for Java”.
So, you can say that Clojure among everything else is my IDE to write Java code. Is that a bad suit for a language? Depends on your perspective, but I personally am very happy that I have Clojure by my side.
Clojure allowed him to build the initial Storm release by himself in only 5 months.
> I made all of Storm's APIs in Java, but implemented Storm in Clojure. By keeping Storm's APIs 100% Java, Storm was ensured to have a very large amount of potential users. By doing the implementation in Clojure, I was able to be a lot more productive and get the project working sooner.
Also interesting is that Nathan has now founded a startup working on something which sounds like the next evolution of Storm, and he's building it in Clojure again:
They recently got 5M in funding and are hiring. Building a Clojure team for it.
Personally, I feel the Storm 2.0 release rewrite to Java is really just a case of the new maintainers not knowing Clojure very well, and being primarily Java devs, looking for contributions from people using Storm, which tend itself to be mostly Java shops. Clojure is not quick to pick up, and very different from Java, so unlike Scala, Kotlin, C#, Go, etc. Someone with a Java background and no Clojure or Lisp experience won't be able to contribute as easily. And that's fine, and possibly best for Storm's future now that Nathan has moved on. Unless a Clojure dev had stepped up and adopted Storm, this change isn't at all surprising.
I just don't understand where there's syntax sugar for propeties in Java. There are lot of unneeded stuff added, that I don't really care about. But my classes are still full of autogenerated getters/setters. I recently tried to find some JEP and I did not find one. There was some talk around Java 7, but nothing since that. Nobody even wants to add properties support for Java?
Interesting how that goes...: the sibling comment to yours said the exact opposite. How does this feature get in your way?
if (this.prop != null) {
this.prop.something() // does not work
}
this.prop?.apply { prop ->
prop.something()
}
2. Interoperation problem. A lot of Java code does not use @Nullable annotations, so all types are just that: platform types. So Kotlin nullability adds nothing to that.
EDIT: to clarify: for example, I consider std::optional as an example of a very "un-OO" type that's immensely useful. In general I like the idea from functional programming that complex types can be treated no different than primitives, rather than the OO way of wrapping and uplifting everything until even integers have methods.
Since when are nulls the biggest problem for developers? Null pointer exceptions are by far some the simplest problems to avoid and/or solve.
There are more serious arguments that can be made in favor of Kotlin.
But they are a problem that happens, and in Kotlin, the compiler checks your nullable logic for you; instead of your users finding the errors at runtime.
People will murder all kinds of productivity to avoid potential NPEs, when as you say they are generally the easiest bugs in the world to contend with.
It is beyond baffling to me, and given how often I hear it, it makes me question the dev world’s sanity.
For this same reason I don't care for NullObject/Maybe/Optional type approaches which simply do not change the branching forking in your code:
if (val == null) { ...logic... }
((Optional) val).ifNull(v -> ...logic...)
Optional to me is a large leap forward. That being said, I also don't like its verbosity and wish for it to be improved somehow.
It usually ends up at odds with better objectives & heavily taxes conscientious developers, for whom we should really be optimizing things imo.
It's not just syntax sugar.
KVM might well turn out to be ART, but that is the extent of it.
For example, the graphical debugger for Kotlin/Native is only available in Clion.
There is even a statement in that regard.
No, many more people know Java than Clojure, that's it. Whether it's the right decision for the future of the project, time will show, but I don't think it was taken lightly.
I disagree on that point. In my experience as a programming language teacher, people often struggle to learn functional programming and even more to learn a Lisp, especially if they are used to a C-like language. And learning both at the same time is even more difficult. I liked working with Clojure but I have yet to meet someone who easily grasps the language and - more important - development patterns.
Would you have any example of what your trainees stumbled upon or found difficult in the language? That would be useful I guess when we try to onboard new people on the project.
Have a nice day :)
Ah, you're mixing up Clojure and Lisp. The restrictions in Clojure have nothing to do with Lisp tradition.
Someone used to a Lisp-like language will also struggle with Clojure.
Traditional Lisps like Common Lisp are multi-paradigm languages in which variables and most aggregate types are mutable.
They are not hard to pick up for someone with a background in C.
C has pass-by-value functions; so does proper, traditional Lisp.
C has mutable variables, arrays and structures; so does Lisp. Lisp data structures like lists or hash tables are easily understandable by a C programmer with a good background in data structures.
cons is like malloc-ing and filling-in a two-field struct, except that freeing is taken care of.
People have written Lisp systems in C (and written more than one book on that exact subject: Nils M. Holm just put a new one out: http://www.t3x.org/lsi/index.html), with a lot of the internals being written in C over the Lisp library functions. E.g. visiting and printing the elements of a list can literally look like this, in the internals of a C-based Lisp implementation:
for (val iter = list; list; list = cdr(list))
print(car(list));
I still see people writing
for(i = 0; i < something; i++) {
}
Meanwhile, I've successfully contributed to plenty of Clojure libraries I use, and many people contribute to my projects. Clojure code is far more direct and concise making it much easier to understand the intent. And majority of the code is written using pure functions that can be reasoned about in isolation. On top of that you have an editor integrated REPL, so you can just run any code you're not sure about as you're reading it.
Just ouf of curiosity, what tools are people using instead of Storm?
But streaming model is more widely adopted outside of frameworks. AWS Lambda or Fass platform can be viewed as streaming model with simple topology.
There's also Kafka Streams which is suitable for many cases that do not warrant a full cluster with all the management and trouble required.
This dynamic will probably never change. Clojure will remain an acquired taste, which is fine, I guess. Those 'in the know' will happily continue to develop effectively with it.
* Non-Java JVM languages are too different for people to use.
Also:
* It's not worth switching from Java to other languages because they're just Java with syntactic sugar.
I misread
> Syntactic sugar does not solve programming problems. Kotlin does not offer any paradigm changes which could make switch worth it.
and
> Also, java 8 and above is getting a lot leaner to use, api, linguistics .. so the gap with clojure is a bit less than before.
Indeed, adopting Clojure for the developer product of this style is a dead end. Clojure is a minority rule. A slow tinkerer's and a lazy (in a good sense) practitioner's tool, whose aim is to survive in a real world, not to show a steady movement no matter what.
I think Clojure's ecosystem is more results-oriented than almost any other currently available[1]. It just requires a completely different mindset to understand, which an average software developer lacks. Therefore, Java is a much better fit for an Apache project.
Since when trying to do better than using a tool designed for mass-producing software with dumb and cheap labor is "falling in love with ideals and tools"? It's kind of like saying that using an excavator over a bunch of people with shovels is "falling in love with ideals and tools". No, it just allows a single person to get more work done faster and better.
Our industry is weird. When recruiting, companies claim they want "the best of the best" and will often test you on ridiculous stuff. But when it comes to actual work, on industry scale, learning, growing professionally, and doing things in a clean and efficient way is frowned upon. Best take the weakest tool available and compensate for its shortcomings with third party services.
This is completely disregarding the available developer pool of Java programmers, and the fact that a lot of them are really talented and can write efficient, production ready software.
The fact is, there is at least an order of magnitude more developers to choose from compared to Closure, and hiring and replacing people is hard. Ignoring business realities like this is bad, and akin to "falling in love with ideals and tools".
Also, someone using Java does not automatically make them dumb cheap programming labour, same as someone using Closure is not automatically going to be a 10xer who has memorised Knuth. It's possible to write bad FP code as well.
I'm not claiming that. I'm claiming that Java has a long history of enabling factory-farming software development, whereas Clojure doesn't lend itself to this style. I mean that in the sense that an army of cheap labor with shovels can, in principle, do the same job as a few trained operators in construction machines. The physics of dirt is the same, and so the job done is essentially the same - just some tools let you do it faster with fewer people. And then, the quantity (or lack of it) has a quality of its own - the more people you engage doing smaller and smaller pieces of work, the more your work becomes about coordinating people than doing the actual job.
(I'm aware that since version 8, Java is growing to be a quite decent programming language. This somewhat weakens my criticism, but not all that much.)
But yeah, I'm also claiming that ceteris paribus, the pool of Clojure developers will yield you higher-skilled programmers on average than the pool of Java programmers - simply because everyone and their dog knows some Java nowadays, and some Java is enough to make some progress in factory-farming software development, whereas Clojure is somewhat atypical and requires expanding your competences beyond the very basics.
(Or, in other words, I'm claiming that the distribution of skill of Java programmers is wider than that of Clojure programmers, with the latter having higher minimum and mean values, and comparable max values.)
Any hugely popular language would have a lot of crap written in it, and a non-popular language wouldn't have "factory-farming" simply because it's not at the needed scale. So any non-mainstream language would almost by definition not lend itself to "factory-farming" development. You could also say that a lot of good stuff has been written in Java, and not as much good stuff has been written in Clojure, and conclude that Clojure doesn't lend itself to writing good stuff.
Any comparison between languages with at least 100x difference in popularity is meaningless, especially as no large bottom-line effect of programming languages has been found.
> the pool of Clojure developers will yield you higher-skilled programmers on average than the pool of Java programmers
Which matters if you're picking people from the pool at random. If not, you want to have the pool with the greater number of higher-skilled developers, not higher average. It's like saying that it makes more sense to start software companies in Finland than in the US, because on average people there are much better educated.
Imagine going from something like lisp to Ada? Or lisp to Rust? Write quick prototypes in lisp, solve the hard problems of understanding the domain, then convert portions that require correctness to a language that is amenable to correctness checking (property testing, model checking, etc).
I think gradual typing [0] (not Gradual Typing) or language embedding [1] are steps in that direction. In a way, lisp can be thought of as a CASE tool for bootstrapping new systems.
The great thing about language platforms (JVM, Beam, Graal, Wasm, Racket) is that many languages can easily exist in the same system so that in many cases, code can be converted on a function by function basis.
But it's in no way inevitable, of course, there are many old Lisp, Python, etc codebases in production too.
BTW. I've been trying to rediscover this blog post and can't seem to find it again, anyone? It described different kinds of software projects, the (1) kind that try to deliver incremental improvements (eg 10% cost savings), and the (2) kind that try to make 10x improvements, and the difference in how those projects are run (the 1-type project can't go over budget because it will then deliver negative value etc).
It is interesting to contrast this with state of affairs in Apache Spark. Spark has thrived well in spite of being a Scala project; Scala arguably has a higher barrier for entry compared to Clojure (although the flavour of Scala used within Spark closely resembles Java).
This is the same pattern, and one should embrace it. Write the first cut, explore the problem space and prototype in a dynamic language. Once the design is proven, rewrite in statically typed language for performance and to get the possible remaining bugs out.
If the design was perfect from the get go, you could just write it in assembler to start with.
It would be interesting to see what the upcoming blogs have to say about the performance gain.
While I appreciate that programmers have limited free time and may not want to learn a new language to contribute to open source, I feel like learning Clojure could be of value to the programmer in itself.
The supposition that Clojure acts as a big barrier against contribution from developers might be true, but I really feel like developers who only write code in the ALGOL family of languages are missing out. Learning a lisp language is not an impossible task and can improve your skills as a developer.
Do they hire developers to maintain and work on the projects? If not, is there community leads in charge of each one? How are they appointed?
I'm curious if the commiters are Clojure developers who chose to switch to Java, or if they are Java devs who decided to rewrite the project to a language they are more familiar and comfortable in. Or if they are Clojure devs looking to transition the project to other commiters and they struggled to find other Clojure devs willing to take it over.
IMO (biased?) Heron makes surprisingly poor design choices for their key distinguishing features like threading model and backpressure. And it shows when you benchmark it. More specifics: https://github.com/apache/storm/pull/2241#issuecomment-31787...
"EOL for 1.0.x With the release of 2.0.0 the 1.0.x version line will no longer be maintained."
Even though Clojure has been Nathan's first-class language, not everyone in contributors and even committers couldn't become native on Clojure. (Though I guess part of committers could feel Clojure as native.) It might not be a problem when Nathan builds most of things in Storm (I'll link his blog post which describes lesson learned from Storm on his perspective http://nathanmarz.com/blog/history-of-apache-storm-and-lesso...), but when Storm becomes popular and also no longer his toy project, Clojure matters for scalibility of the project.
Personally, I had a hard time understanding plenty of macros and even chained macros - that might not be a problem if I were allowed to have plenty of times to study Clojure and get used to it, but possible contributors don't get a chance when they're ready. In many cases, the first time they read the code on what they're using is when they encounter issues on stage/production and have to dig with stack trace. For me, I had to investigate on Storm because my team suffered from lack of documentation and also lack of knowledge on internal which ended up just taking workarounds. It was pretty hard time learning language to just read and understand the details to track down the issue. I even couldn't think of writing code on Clojure.
When I decided to contribute Apache Storm, I started from connectors and CI build which wasn't written on Clojure. After some months I was able to read and understand the code to get into details but I still couldn't be native for Clojure, so still required N times of efforts to read and write the code even after I became one of PMC member.
Don't get me wrong. I'm not saying something is better than some other one. In scalability point of view on project, I guess we had to do this, even though it ended up teaching me some lesson that migrating language is not the thing which can be considered easily, especially for a big project. Lots of efforts were spent here.
Someone could claim for Apache Spark's case for Scala. Yes, I'm also contributing to Apache Spark and I had to learn Scala (fortunately I had a chance to do that before contributing) but the case is different. If you read Databricks Scala guide in details, you might realize that the doc is actually not encouraging contributors to use advanced features (a.k.a the features only Scala geeks might feel natural) on Scala. Same goes on reading codebase. Apache Spark community has been trying to keep necessary knowledges on Scala to contribute Apache Spark low enough, so that non-expert of Scala engineer could easily try out contribution. If they have been requiring hard understanding of Scala to accept contributions - Spark may not be able to get its amazing reputation.
Almost every one of the ~100 comments is in response to the original title that Storm switched from Clojure to Java. Now this context is lost.
Another example would be "Press release from XYZ". If it talks about XYZ reaching some major breakthrough, the title should be allowed to reflect that. It's a waste of everyone's time to post the article titled "Press release".
And arguably this situation should fall under such an exception.
This was mentioned briefly here: https://hortonworks.com/blog/microbenchmarking-storm-1-0-per...
The Clojure based core has served the community well for some time. It was still powered by Disruptor (a fast Java messaging library). So there was always some back and forth between Java and Clojure.
For Storm 2.0, the Java rewrite happened first. The re-architecture work might have not happened without it (at least for the foreseeable near future)... primarily due to Java expertise being more easily available.