3 ms·

Even if one of these constructs is faster it doesn't matter 99% of the time. Writing well structured readable code is typically far more important than making

Even if one of these constructs is faster it doesn't matter 99% of the time. Writing well structured readable code is typically far more important than making it twice as fast. And those times can rarely be predicted beforehand, so you should mostly not worry about it until you see real performance problems.

tombert 3y ago
I mostly focus on "using stuff that won't break", and yeah "if it actually matters". For example, much to the annoyance of a lot of people, I don't typically use floating point numbers when I start out. I will use the "decimal" or "money" types of the language, or GMP if I'm using C. When I do that, I can be sure that I won't have to worry about any kind of funky overflow issues or bizarre rounding problems. There might be a performance overhead associated with it, but then I have to ask myself "how often is this actually called?" If the answer is "a billion times" or "once in every iteration of the event loop" or something, then I will probably eventually go back and figure out if I can use a float or convert it to an integer-based thing, but in a lot of cases the answer is "like ten or twenty times", and at that point I'm not even 100% sure it would be even measurable to change to the "faster" implementations. What annoys me is that people will act like they really care about speed, do all these annoying micro-optimizations, and then forget that pretty much all of them get wiped out immediately upon hitting the network, since the latency associated with that is obscene.
apantel 3y ago
The counter-argument to this is if you are building something that is in the critical path of an application (for example, parsing HTTP in a web server), you need to be performance-minded from the beginning because design decisions lead to design decisions. If you are building something in the critical path of the application, the best thing to do is build it from the ground up measuring the performance of what you have as you go. This way, each time you add something you will see the performance impact and usually there’s a more performant way of doing something that isn’t more obscure. If you do this as you build, early choices become constraints, but because you chose the most performant thing at every stage, the whole process takes you in the direction of a highly-performant implementation. Why should you care about performance? I can give you my personal experience: I’ve been working on a Java web/application server for the past 15 years and a typical request (only reading, not writing to the db) would take maybe 4-5 ms to execute. That includes HTTP request parsing, JSON parsing, session validation, method execution, JSON serialization, and HTTP response dispatch. Over the past 9 months I have refactored the entire application for performance and a typical request now takes about 0.25 ms or 250 microseconds. The computer is doing so much less work to accomplish the same tasks, it’s almost silly how much work it was doing before. And the result is the machine can handle 20x more requests in the same amount of time. If it could handle 200 requests per second per core before, now it can handle 4000. That means the need to scale is felt 20x less intensely, which means less complexity around scaling. High performance means reduced scaling requirements.
- tombert 3y ago
  But even that sort of depends right? Hardware is often pretty cheap in comparison to dev-time. I really depends on the project, what kind of servers you're using, the nature of the application etc, but I think a lot of the time it might be cheaper to just pay for 20x the servers than it would be to pay a human to go find a critical path. I'm not saying you completely throw caution to the wind, I'm just saying that there's a finite amount of human resources and it can really vary how you want to allocate them. Sometimes the better path is to just throw money at the problem. It really depends.
  - apantel 3y ago
    I think it depends on what you’re building and who’s building it. We’re all benefitting from the fact that the designers of NGINX made performance a priority. We like using things that were designed to be performant. We like high-FPS games. We like fast internet. I personally don’t like the idea of throwing compute at a slow solution. I like when the extra effort has been put into something. The good feeling I get from interacting with something that is optimal or excellent is an end in itself and one of the things I live for.
    - tombert 3y ago
      Sure, though I've mentioned a few times in this thread now that the thing that bothers me more than CPU optimizations is not taking into account latency, particularly when hitting the network, and I think focusing on that will generally pay higher dividends than trying to optimize for processing. CPUs are ridiculously fast now, and compilers are really really good now too. I'm not going to say that processing speed is a "solved" problem, but I am going to say that in a lot of performance-related cases the CPU processing is probably not your problem. I will admit that this kind of pokes holes in my previous response, because introducing more machines into the mix will almost certainly increase latency, but I think it more or less holds depending on context. But I think it really is a matter of nuance, which you hinted at. If I'm making an admin screen that's going to have like a dozen users max, then a slow, crappy solution is probably fine; the requests will be served fast enough to where no one will notice anyway, and you can probably even get away with the cheapest machine/VM. If I'm making an FPS game that has 100,000 concurrent users, then it almost certainly will be beneficial to squeeze out as much performance out of the machine as possible, both CPU and latency-wise. But as I keep repeating everywhere, you have to measure. You cannot assume that your intuition is going to be right, particularly at-scale.
neonsunset 3y ago
This attitude is part of the problem. Another part of the problem is having no idea which things actually end up costing performance and how much. It is why many language ecosystems suffered from performance issues for a really long time even if completely unwarranted. Is changing ifs to switch or vice versa, as outlined in the post above, a waste of time? Yes, unless you are writing some encoding algorithm or a parser, it will not matter. The compiler will lower trivial statements to the same codegen and it will not impact the resulting performance anyway even if there was difference given a problem the code was solving. However, there are things that do cost like interface spam, abusing lambdas writing needlessly complex wokflow-style patterns (which are also less readable and worse in 8 out of 10 instances), not caching objects that always have the same value, etc. These kinds of issues, for example, plagued .NET ecosystem until more recent culture shift where it started to be cool once again to focus on performance. It wasn't being helped by the notion of "well-structured code" being just idiotic "clean architecture" and "GoF patterns" style dogma applied to smallest applications and simplest of business domains. (it is also the reason why picking slow languages in general is a really bad idea - everything costs more and you have way less leeway for no productivity win - Ruby and Python, and JS with Node.js are less productive to write in than C#/F#, Kotlin/Java or Go(under some conditions))
- tombert 3y ago
  I mean, that's kind of why I tried to emphasize measuring things yourself instead of depending on tribal knowledge. There are plenty of cases where even the "slow" implementation is more than fast enough, and there are also plenty of cases where the "correct" solution (from a big-O or intuition perspective) is actually slower than the dumb case. Intuition helps, you have to measure and/or look at the compiled results if you want to ensure correct numbers. An example that really annoys me is how every whiteboard interview ends up being "interesting ways to use a hashmap", which isn't inherently an issue, but they will usually be so small-scoped that an iterative "array of pairs" might actually be cheaper than paying the up-front cost of hashing and potentially dealing with collisions. Interviews almost always ignore constant factors, and that's fair enough, but in reality constant factors can matter, and we're training future employees to ignore that. I'll say it again: as far as I can tell, you have to measure if you want to know if your result is "faster". "Measuring" might involve memory profilers, or dumb timers, or a mixture of both. Gut instincts are often wrong.

tombert 3y ago

I mostly focus on "using stuff that won't break", and yeah "if it actually matters". For example, much to the annoyance of a lot of people, I don't typically use floating point numbers when I start out. I will use the "decimal" or "money" types of the language, or GMP if I'm using C. When I do that, I can be sure that I won't have to worry about any kind of funky overflow issues or bizarre rounding problems. There might be a performance overhead associated with it, but then I have to ask myself "how often is this actually called?" If the answer is "a billion times" or "once in every iteration of the event loop" or something, then I will probably eventually go back and figure out if I can use a float or convert it to an integer-based thing, but in a lot of cases the answer is "like ten or twenty times", and at that point I'm not even 100% sure it would be even measurable to change to the "faster" implementations. What annoys me is that people will act like they really care about speed, do all these annoying micro-optimizations, and then forget that pretty much all of them get wiped out immediately upon hitting the network, since the latency associated with that is obscene.

apantel 3y ago

The counter-argument to this is if you are building something that is in the critical path of an application (for example, parsing HTTP in a web server), you need to be performance-minded from the beginning because design decisions lead to design decisions. If you are building something in the critical path of the application, the best thing to do is build it from the ground up measuring the performance of what you have as you go. This way, each time you add something you will see the performance impact and usually there’s a more performant way of doing something that isn’t more obscure. If you do this as you build, early choices become constraints, but because you chose the most performant thing at every stage, the whole process takes you in the direction of a highly-performant implementation. Why should you care about performance? I can give you my personal experience: I’ve been working on a Java web/application server for the past 15 years and a typical request (only reading, not writing to the db) would take maybe 4-5 ms to execute. That includes HTTP request parsing, JSON parsing, session validation, method execution, JSON serialization, and HTTP response dispatch. Over the past 9 months I have refactored the entire application for performance and a typical request now takes about 0.25 ms or 250 microseconds. The computer is doing so much less work to accomplish the same tasks, it’s almost silly how much work it was doing before. And the result is the machine can handle 20x more requests in the same amount of time. If it could handle 200 requests per second per core before, now it can handle 4000. That means the need to scale is felt 20x less intensely, which means less complexity around scaling. High performance means reduced scaling requirements.

tombert 3y ago
But even that sort of depends right? Hardware is often pretty cheap in comparison to dev-time. I really depends on the project, what kind of servers you're using, the nature of the application etc, but I think a lot of the time it might be cheaper to just pay for 20x the servers than it would be to pay a human to go find a critical path. I'm not saying you completely throw caution to the wind, I'm just saying that there's a finite amount of human resources and it can really vary how you want to allocate them. Sometimes the better path is to just throw money at the problem. It really depends.
- apantel 3y ago
  I think it depends on what you’re building and who’s building it. We’re all benefitting from the fact that the designers of NGINX made performance a priority. We like using things that were designed to be performant. We like high-FPS games. We like fast internet. I personally don’t like the idea of throwing compute at a slow solution. I like when the extra effort has been put into something. The good feeling I get from interacting with something that is optimal or excellent is an end in itself and one of the things I live for.
  - tombert 3y ago
    Sure, though I've mentioned a few times in this thread now that the thing that bothers me more than CPU optimizations is not taking into account latency, particularly when hitting the network, and I think focusing on that will generally pay higher dividends than trying to optimize for processing. CPUs are ridiculously fast now, and compilers are really really good now too. I'm not going to say that processing speed is a "solved" problem, but I am going to say that in a lot of performance-related cases the CPU processing is probably not your problem. I will admit that this kind of pokes holes in my previous response, because introducing more machines into the mix will almost certainly increase latency, but I think it more or less holds depending on context. But I think it really is a matter of nuance, which you hinted at. If I'm making an admin screen that's going to have like a dozen users max, then a slow, crappy solution is probably fine; the requests will be served fast enough to where no one will notice anyway, and you can probably even get away with the cheapest machine/VM. If I'm making an FPS game that has 100,000 concurrent users, then it almost certainly will be beneficial to squeeze out as much performance out of the machine as possible, both CPU and latency-wise. But as I keep repeating everywhere, you have to measure. You cannot assume that your intuition is going to be right, particularly at-scale.

neonsunset 3y ago

This attitude is part of the problem. Another part of the problem is having no idea which things actually end up costing performance and how much. It is why many language ecosystems suffered from performance issues for a really long time even if completely unwarranted. Is changing ifs to switch or vice versa, as outlined in the post above, a waste of time? Yes, unless you are writing some encoding algorithm or a parser, it will not matter. The compiler will lower trivial statements to the same codegen and it will not impact the resulting performance anyway even if there was difference given a problem the code was solving. However, there are things that do cost like interface spam, abusing lambdas writing needlessly complex wokflow-style patterns (which are also less readable and worse in 8 out of 10 instances), not caching objects that always have the same value, etc. These kinds of issues, for example, plagued .NET ecosystem until more recent culture shift where it started to be cool once again to focus on performance. It wasn't being helped by the notion of "well-structured code" being just idiotic "clean architecture" and "GoF patterns" style dogma applied to smallest applications and simplest of business domains. (it is also the reason why picking slow languages in general is a really bad idea - everything costs more and you have way less leeway for no productivity win - Ruby and Python, and JS with Node.js are less productive to write in than C#/F#, Kotlin/Java or Go(under some conditions))

tombert 3y ago
I mean, that's kind of why I tried to emphasize measuring things yourself instead of depending on tribal knowledge. There are plenty of cases where even the "slow" implementation is more than fast enough, and there are also plenty of cases where the "correct" solution (from a big-O or intuition perspective) is actually slower than the dumb case. Intuition helps, you have to measure and/or look at the compiled results if you want to ensure correct numbers. An example that really annoys me is how every whiteboard interview ends up being "interesting ways to use a hashmap", which isn't inherently an issue, but they will usually be so small-scoped that an iterative "array of pairs" might actually be cheaper than paying the up-front cost of hashing and potentially dealing with collisions. Interviews almost always ignore constant factors, and that's fair enough, but in reality constant factors can matter, and we're training future employees to ignore that. I'll say it again: as far as I can tell, you have to measure if you want to know if your result is "faster". "Measuring" might involve memory profilers, or dumb timers, or a mixture of both. Gut instincts are often wrong.