Source: C:\Users\u ser\Deskto p\ActivePe rl-5.24.1. I cover some in Mastering Perl and Effective Perl Programming.Checks for available system drives (often done to infect USB drives) There are many more, but it's too early in the morning to figure out what those are. But being as this is Perl, the most powerful language in the world, and would blow your memory clean off, you've got to ask yourself one question: Do I feel lucky? Well, do ya, punk? ☹ Did he use 6 Gb or only five? Well, to tell you the truth, in all this excitement I kind of lost track myself. This program doesn't even need to be on the same box. ![]() When that other program is done, all of its memory returns to the operating system. If you have a have processing task that will use a big chunk of memory, let a different program (perhaps a fork of the current program) handle that and give you back the answer. ☹ Use external programs, forks, job queues, or other separate actors so you don't have to carry around short-term memory burdens. You can optimize the tail problem yourself with tricks with goto or a module, but that's a lot of work to hang onto a technique that you probably don't need. Perl doesn't have tail recursion optimization, so every new call adds to the call stack. ☹ Turn recursive solutions into iterative ones. Similarly, work distribution systems, such as Minion, can spread work out among machines. When you get the answer, the child process shuts down and releases it memory. ![]() ![]() The child process only has the memory footprint while it's working. ☹ If you need to handle a big chunk of data once but don't want the persistent memory footprint, offload the work to a child process. I found a patch in the module's RT queue, applied it, and solved the problem. I had big problems with an application until I realized that a module wasn't releasing memory. This goes both ways as subroutine arguments and subroutine return values: call_some_sub( \$big_text, ) If you have to copy it because you want to change something, you might be stuck. ☹ ( Update: Perl can now handle this for you in most cases because it uses a Copy On Write (COW) mechanism) Pass large chunks of text and large aggregates by reference so you don't make a copy, thus storing the same information twice. Whenever I've done that, I've reduced the memory footprint by about 100%. Outside of Perl, there are various key-value stores, such as Redis, that may help. ☹ If you need to create big data structures, consider something like DBM::Deep or other storage engines to keep most of it out of RAM and on disk until you need it. Memory-map files instead of slurping them ☹ You might not even need to have the file in memory. foreach ( ) # scalar context, line by line If you only need it line-by-line, use while. For instance, reading a file with a foreach reads all the input at once. ☹ Avoid creating big temporary structures. ☹ Use lexical variables with the smallest scope possible to allow Perl to re-use that memory when you don't need it. See Profiling heap memory usage on perl programs and How to find the amount of physical memory occupied by a hash in Perl? ☹ Use Perl memory profiling tools to help you find problem areas. This is not a comprehensive list (and there's more in Programming Perl): ![]() memory, might negatively impact another, such as speed. Realize that optimizing in one direction, e.g. In general, Perl holds on to any memory you use, even if it's not using it. What sort of problem are you running into, and what does "large" mean to you? I have friends you need to load 200 Gb files into memory, so their idea of good tips is a lot different than the budget shopper for minimal VM slices suffering with 250 Mb of RAM (really? My phone has more than that).
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