4 ms·
From what I can see, the myth that needs to be debunked isn't that garbage collection is super fast and easy with no consequences, it's the myth that garbage co
by jerf 4y ago
From what I can see, the myth that needs to be debunked isn't that garbage collection is super fast and easy with no consequences, it's the myth that garbage collection always automatically means your program is going to be spending 80% of its time doing it and freezing for a second every five seconds the instant you use a language with garbage collection. I see far more "I'm writing a web server that's going to handle six requests every hour but I'm afraid the garbage collector is going to trash my performance" than people who believe it's magically free.
It's just another engineering decision. On modern systems, and especially with any runtime that can do the majority of the GC threaded and on an otherwise-unused core, you need to have some pretty serious performance requirements for GC to ever get to being your biggest problem. You should almost always know when you're setting out to write such a system, and then, sure, think about the GC strategy and its costs. However for the vast bulk of programs the correct solution is to spend on the order of 10 seconds thinking about it and realizing that the performance costs of any memory management solution are trivial and irrelevant and the only issue in the conversation is what benefits you get from the various options and what the non-performance costs are.
It is in some sense as big a mistake (proportional to the program size) to write every little program like it's a AAA game as it is to write a AAA game as if it's just some tiny little project, but by the sheer overwhelming preponderance of programming problems that are less complicated than AAA games, the former happens overwhelmingly more often than the latter.
Edit: I can be specific. I just greased up one of my production systems with Go memstats. It periodically scans XML files via network requests and parses them with a parser that cross-links parents, siblings, and children using pointers and then runs a lot of XPath on them, so, it's kinda pessimal behavior for a GC. I tortured it far out of its normal CPU range by calling the "give me all your data" JSON dump a 100 times. I've clicked around on the website it serves to put load on it a good 10x what it would normally see in an hour, minimum. In 15 minutes of this way-above-normal use, it has so far paused my program for 14.6 milliseconds total. If you straight-up added 14.6 milliseconds of latency to every page it scanned, every processing operation, and every web page I loaded, I literally wouldn't be able to notice, and of course that's not what actually happened. Every second worrying about GC on this system would be wasted.
- nickbauman 4y agoYes; I have a friend who is part of a small team that wrote a very successful stock market trading gateway in Java. Turns out the JVM's GC can be tuned in very specific ways based on your needs. And there are ways to avoid having to do JVM GC in critical areas of the code as well.
- PaulHoule 4y agoGenerally Java has made a huge investment in the garbage collector over a long period of time to address the problems that people have in some use cases. JDK 17 is much better than JDK 8. If you were writing a GC from scratch you are not going to do as well.
- hinkley 4y agoTo be fair, they definitely got into a rut in the JDK 6-7 timeframe. I maintain it's no accident that memcache came into its own during this period. That was a major pain point, and going out-of-process shouldn't have been necessary.
- bcrosby95 4y agoI always figured memcached gained popularity because it let your monolithic LAMP-like-stack scale better, not because of anything about Java. Just wedge it between your N stateless application servers and MySQL and you could handle 10x more users. At least, that's how most people I knew back in 2006ish were using it.
- hinkley 4y agoI think each ecosystem had a very different experience with memcached adoption. In Java it was really limiting to do in process cache, and that limitation hit a wall while memcached usage was starting to spread. I assume Rails and maybe Python had similar problems, because all of the papers about GC techniques up to about that point were talking about Java. They got a lot of good stuff first or second. What’s common though is that hard drives were not getting faster, but network hardware was hitting its stride. Full bandwidth (port speed X port count) routers and multi NIC were recently ubiquitous. I had just come off a carrier grade software project when memcached finally hit my radar, and we had only spec’ed 3-5 servers for the web tier. That was still enough local cache hit rate to keep us running relatively smoothly. Or at least once we got done being honorary QA members for F5. We had lots of problems on that project with data modeling and so we actually were using too much caching vs precalculation but that’s a different story.