这是一个超级简化版的傻瓜。

当对象在内存中创建时，它们被添加到内存中已使用部分的末尾。

如果一个对象不在已使用内存部分的末尾被删除，这意味着这个对象位于其他两个对象之间，它将创建一个“洞”。

这就是所谓的碎片化。

什么是内存碎片?

内存碎片是指当您的大部分内存被分配为大量不连续的块或块时——留下很大比例的内存未分配，但在大多数典型场景下无法使用。这将导致内存溢出异常或分配错误(即malloc返回null)。

The easiest way to think about this is to imagine you have a big empty wall that you need to put pictures of varying sizes on. Each picture takes up a certain size and you obviously can't split it into smaller pieces to make it fit. You need an empty spot on the wall, the size of the picture, or else you can't put it up. Now, if you start hanging pictures on the wall and you're not careful about how you arrange them, you will soon end up with a wall that's partially covered with pictures and even though you may have empty spots most new pictures won't fit because they're larger than the available spots. You can still hang really small pictures, but most ones won't fit. So you'll have to re-arrange (compact) the ones already on the wall to make room for more..

现在，想象墙是你的(堆)内存，图片是物体。这就是内存碎片。

如何判断内存碎片是否是我的应用程序的一个问题?什么样的程序最可能受到影响?

您可能正在处理内存碎片的一个明显迹象是，如果您得到许多分配错误，特别是当已使用内存的百分比很高时(但不是您还没有使用完所有内存)，那么从技术上讲，您应该有足够的空间用于您试图分配的对象。

当内存严重碎片化时，内存分配可能需要更长的时间，因为内存分配器必须做更多的工作来为新对象找到合适的空间。如果您有许多内存分配(您可能会这样做，因为您最终会产生内存碎片)，分配时间甚至可能会导致明显的延迟。

处理内存碎片的常用方法是什么?

使用好的算法分配内存。不是为许多小对象分配内存，而是为这些小对象的连续数组预分配内存。有时，在分配内存时稍微浪费一点可以提高性能，并且可以省去必须处理内存碎片的麻烦。

什么是内存碎片?

Memory fragmentation is the problem of memory becoming unusable even though it is theoretically available. There are two kinds of fragmentation: internal fragmentation is memory that is allocated but cannot be used (e.g. when memory is allocated in 8 byte chunks but the program repeatedly does single allocations when it needs only 4 bytes). external fragmentation is the problem of free memory becoming divided into many small chunks so that large allocation requests cannot be met although there is enough overall free memory.

如何判断内存碎片是否是我的应用程序的一个问题?什么样的程序最可能受到影响?

如果您的程序使用的系统内存远远超过其实际有效负载数据所需的内存(并且您已经排除了内存泄漏)，那么内存碎片就是一个问题。

处理内存碎片的常用方法是什么?

使用一个好的内存分配器。在IIRC中，那些使用“最佳匹配”策略的人通常在避免碎片化方面要出色得多，只是速度稍慢一些。然而，事实也表明，对于任何配置策略，都存在病态的最坏情况。幸运的是，对于分配器来说，大多数应用程序的典型分配模式实际上是相对友好的。如果你对细节感兴趣，这里有一堆文件:

Paul R. Wilson, Mark S. Johnstone, Michael Neely and David Boles. Dynamic Storage Allocation: A Survey and Critical Review. In Proceedings of the 1995 International Workshop on Memory Management, Springer Verlag LNCS, 1995 Mark S.Johnstone, Paul R. Wilson. The Memory Fragmentation Problem: Solved? In ACM SIG-PLAN Notices, volume 34 No. 3, pages 26-36, 1999 M.R. Garey, R.L. Graham and J.D. Ullman. Worst-Case analysis of memory allocation algorithms. In Fourth Annual ACM Symposium on the Theory of Computing, 1972

更新: 谷歌TCMalloc:线程缓存Malloc 已经发现它在处理长时间运行进程中的碎片方面相当出色。

我一直在开发一个服务器应用程序，它在HP-UX 11.23/11.31 ia64上存在内存碎片问题。

它是这样的。有一个进程进行内存分配和释放，并运行了几天。即使没有内存泄漏，进程的内存消耗也在不断增加。

About my experience. On HP-UX it is very easy to find memory fragmentation using HP-UX gdb. You set a break-point and when you hit it you run this command: info heap and see all memory allocations for the process and the total size of heap. Then your continue your program and then some time later your again hit the break-point. You do again info heap. If the total size of heap is bigger but the number and the size of separate allocations are the same then it is likely that you have memory allocation problems. If necessary do this check few fore times.

My way of improving the situation was this. After I had done some analysis with HP-UX gdb I saw that memory problems were caused by the fact that I used std::vector for storing some types of information from a database. std::vector requires that its data must be kept in one block. I had a few containers based on std::vector. These containers were regularly recreated. There were often situations when new records were added to the database and after that the containers were recreated. And since the recreated containers were bigger their did not fit into available blocks of free memory and the runtime asked for a new bigger block from the OS. As a result even though there were no memory leaks the memory consumption of the process grew. I improved the situation when I changed the containers. Instead of std::vector I started using std::deque which has a different way of allocating memory for data.

我知道在HP-UX上避免内存碎片的方法之一是使用小块分配器或使用MallocNextGen。在RedHat Linux上，默认的分配器似乎可以很好地处理大量小块的分配。在Windows上有低碎片堆，它解决了大量小分配的问题。

My understanding is that in an STL-heavy application you have first to identify problems. Memory allocators (like in libc) actually handle the problem of a lot of small allocations, which is typical for std::string (for instance in my server application there are lots of STL strings but as I see from running info heap they are not causing any problems). My impression is that you need to avoid frequent large allocations. Unfortunately there are situations when you can't avoid them and have to change your code. As I say in my case I improved the situation when switched to std::deque. If you identify your memory fragmention it might be possible to talk about it more precisely.

关于内存碎片的详细答案可以在这里找到。

http://library.softwareverify.com/memory-fragmentation-your-worst-nightmare/

这是11年来我一直在softwareverify.com上回答人们关于内存碎片问题的答案的高潮

假设你有一个“大”(32字节)的空闲内存:

----------------------------------
|                                |
----------------------------------

现在，分配其中的一些(5个分配):

----------------------------------
|aaaabbccccccddeeee              |
----------------------------------

现在，释放前四个分配，但不释放第五个:

----------------------------------
|              eeee              |
----------------------------------

现在，尝试分配16个字节。哦，我不能，尽管有近两倍的免费。

在具有虚拟内存的系统上，碎片并不是您想象的那么大的问题，因为大的分配只需要在虚拟地址空间中连续，而不需要在物理地址空间中连续。所以在我的例子中，如果我有一个页面大小为2字节的虚拟内存，那么我可以毫无问题地分配16字节。物理内存看起来是这样的:

----------------------------------
|ffffffffffffffeeeeff            |
----------------------------------

而虚拟内存(要大得多)可能是这样的:

------------------------------------------------------...
|              eeeeffffffffffffffff                   
------------------------------------------------------...

内存碎片的典型症状是，您试图分配一个大块，但您不能，即使您看起来有足够的空闲内存。另一个可能的后果是进程无法将内存释放回操作系统(因为它从操作系统中分配给malloc等进行细分的每个大块中都有一些剩余的东西，即使每个块的大部分现在都没有使用)。

Tactics to prevent memory fragmentation in C++ work by allocating objects from different areas according to their size and/or their expected lifetime. So if you're going to create a lot of objects and destroy them all together later, allocate them from a memory pool. Any other allocations you do in between them won't be from the pool, hence won't be located in between them in memory, so memory will not be fragmented as a result. Or, if you're going to allocate a lot of objects of the same size then allocate them from the same pool. Then a stretch of free space in the pool can never be smaller than the size you're trying to allocate from that pool.

一般来说，您不需要太担心它，除非您的程序是长时间运行的，并且进行了大量的分配和释放。当您同时拥有短寿命和长寿命对象时，您的风险最大，但即使在这种情况下，malloc也会尽最大努力提供帮助。基本上，忽略它，直到您的程序出现分配失败或意外地导致系统内存不足(在测试中捕获它，这是首选!)。

标准库并不比其他任何分配内存的工具差，标准容器都有一个Alloc模板参数，如果绝对必要，您可以使用它来微调它们的分配策略。