使用heap profiler进行内存占用分析

　　最近在项目中用到了google的heap profiler工具来分析内存占用，效果非常显著，因此在这里写一篇博客记录一下使用过程中遇到的一些问题。

heap profiler依赖于tcmalloc，所以先要在本机安装tcmalloc，安装过程非常的简单。然后开始使用tcmalloc进行编译自己写的程序。

• 生成堆栈快照

先写一段申请大量内存的代码：

heap_profiler.cpp

   #include <iostream>
   #include <unistd.h>
 
   int* create(unsigned int size)
   {
       return new int[size];
   }
 
   int main()
  {
      int count = ;
      int* array[count];
 
      unsigned int size =  * ;
      for (int i = ; i < count; ++i) {
          sleep();
          array[i] = create( * size);
 
          int* b = new int[ * size];
      }                       
 
      for (int i = ; i < count; ++i) {
          delete[] array[i];
      }
  }

接着进行编译：

$ g++ heap_profiler.cpp -ltcmalloc -g -o main

然后执行如下命令：

$ HEAPPROFILE=test ./main
Starting tracking the heap
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap (Exiting,  MB in use)
$ ls
heap_profiler.cpp  main  test..heap  test..heap  test..heap  test..heap  test..heap

可以看到，这里生成了几个.heap文件，并且知道程序退出时，还有80M的内存在未释放。使用pprof命令即可对这些文件进行分析。

这里需要特别注意一点，笔者之前因为项目本身用的tcmalloc是采用静态链接方式，即如下所示，编译时，静态链接了static_lib下的libtcmalloc.a：

$ ls -lh
total .0K
-rw-rw-r--  minglee minglee   Dec  : heap_profiler.cpp
drwxrwxr-x  minglee minglee .0K Dec  : static_lib
 
$ ls -lh static_lib/
total 5.7M
-rw-rw-r--  minglee minglee 5.6M Dec  : libtcmalloc.a
 
$ g++ heap_profiler.cpp -ltcmalloc -g -o main -Lstatic_lib/ -lpthread
static_lib//libtcmalloc.a(stacktrace.o): In function `GetStackTraceWithContext_libunwind(void**, int, int, void const*)':
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_Ux86_64_getcontext'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_init_local'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_step'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_step'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_get_reg'
static_lib//libtcmalloc.a(stacktrace.o): In function `GetStackTrace_libunwind(void**, int, int)':
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_Ux86_64_getcontext'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_init_local'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_step'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_step'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_get_reg'
static_lib//libtcmalloc.a(stacktrace.o): In function `GetStackFramesWithContext_libunwind(void**, int*, int, int, void const*)':
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_Ux86_64_getcontext'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_init_local'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_step'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_get_reg'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_step'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_get_reg'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_get_reg'
static_lib//libtcmalloc.a(stacktrace.o): In function `GetStackFrames_libunwind(void**, int*, int, int)':
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_Ux86_64_getcontext'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_init_local'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_step'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_get_reg'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_step'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_get_reg'
/home/minglee/install_packet/gperftools-2.7/src/stacktrace_libunwind-inl.h:: undefined reference to `_ULx86_64_get_reg'
collect2: error: ld returned  exit status
 
$ g++ heap_profiler.cpp -ltcmalloc -g -o main -Lstatic_lib/ -lpthread -lunwind
 
$ HEAPPROFILE=test ./main
$ 

导致执行的时候没有任何的反应，也不会出现 “Starting tracking the heap” 提示，更不会生成 .heap 文件。所以切记使用heap_profiler的时候需要使用动态链接，如果不想使用动态链接，也可以通过加代码的方式去生成.heap文件：

   #include <iostream>
   #include <unistd.h>
   #include <gperftools/heap-profiler.h>
 
   int* create(unsigned int size)
   {
       return new int[size];
   }
 
  int main()
  {
      HeapProfilerStart("test");
      int count = ;
      int* array[count];
 
      unsigned int size =  *  * ;
      for (int i = ; i < count; ++i) {
          sleep();
          array[i] = create(size);
 
          int* b = new int[2 * size];
      }
 
      for (int i = ; i < count; ++i) {
          delete[] array[i];
      }
      HeapProfilerStop();
  }

注意 第12行 和 第27行 增加的两个函数，HeapProfilerStart() 和 HeapProfilerStop()（头文件在<gperftools/heap-profiler.h>中），分别用来开启和关闭堆栈分析器，HeapProfilerStart() 需要一个参数，这个参数就是.heap文件（也就是堆栈快照）的前缀。这个前缀也可以通过环境变量 HEAPPROFILE 来设置。这也编译出来的代码，直接执行，也可以生产.heap文件：

$ g++ heap_profiler.cpp -ltcmalloc -g -o main -Lstatic_lib/ -lpthread -lunwind
$ ./main
Starting tracking the heap
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)

可以看到，使用动态编译的方式libtcmalloc的方式来使用heap profiler能显示出更多的信息，比如程序退出时是否有未释放的内存。以下的分析阶段都是采用动态编译的方式进行。

• 使用pprof命令进行分析：

$ HEAPPROFILE=test ./main
Starting tracking the heap
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap ( MB currently in use)
Dumping heap profile to test..heap (Exiting,  MB in use)
$ pprof --text main test..heap
Using local file main.
Using local file test..heap.
Total: 480.0 MB
   400.0  83.3%  83.3%    400.0  83.3% create
    80.0  16.7% 100.0%    480.0 100.0% main
     0.0   0.0% 100.0%    480.0 100.0% __libc_start_main

可以很清晰的看到内存分配的函数以及分配的内存总量。各列含义的解读：

• 第一列包含直接占用的内存
• 第四列包含自身和所有被调用的函数占用的内存
• 第二列和第五列仅仅是第一列和第四列数字的百分比表示
• 第三列是第二列从第一行到当前行的累加值。（比如：二行三列= 一行二列 + 二行二列； 三行三列 = 一行二列 + 二行二列 + 三行二列）

另外还可以加上--stack选项（与--text同时使用）：

$ pprof --text --stack main test..heap
Using local file main.
Using local file test..heap.
Total: 480.0 MB
Stacks:
 
 (00000000004009aa) /home/minglee/workspace/test_code/heap_profiler/heap_profiler.cpp::main
         (00007f9644cb3c04) ??::__libc_start_main
 
 (00000000004008b8) /home/minglee/workspace/test_code/heap_profiler/heap_profiler.cpp::create
         (000000000040096d) /home/minglee/workspace/test_code/heap_profiler/heap_profiler.cpp::main
         (00007f9644cb3c04) ??::__libc_start_main
 
Leak of  bytes in  objects allocated from:
    @ 004008b8 unknown
    @ 000000000040096d main /home/minglee/workspace/test_code/heap_profiler/heap_profiler.cpp:
    @ 00007f9644cb3c04 __libc_start_main ??:
Leak of  bytes in  objects allocated from:
    @ 004009aa unknown
    @ 00007f9644cb3c04 __libc_start_main ??:
 
   400.0  83.3%  83.3%    400.0  83.3% create
    80.0  16.7% 100.0%    480.0 100.0% main
     0.0   0.0% 100.0%    480.0 100.0% __libc_start_main

--text的选项，在查看简单的程序时还是不错的，但是面对复杂的程序时，就显得心有余力不足了。这个时候可以使用--gv选项：

$ pprof --gv main test..heap
Using local file main.
Using local file test..heap.
Dropping nodes with <= 2.4 MB; edges with <= 0.5 abs(MB)
sh: dot: command not found

这里报错是因为--gv选项需要安装 graphviz 和 gv：

$ sudo yum install graphviz gv

安装完之后如果报出如下错误：

$ pprof --gv main test..heap
Using local file main.
Using local file test..heap.
Dropping nodes with <= 2.4 MB; edges with <= 0.5 abs(MB)
gv: Unable to open the display.

说明无法打开显示器，也就是说，--gv选项，需要在带图形界面的系统上使用。转到图形界面系统上做分析，可以得到下图：

可以看到main函数占用了80M内存，占所有占用内存的16.7%，main直接或间接占用了内存480M，占所有未释放内存的100%，下面的create函数占用内存400M，占所有未释放内存的83.3%。显示的结果非常清晰明了，能够清晰的定位到问题。

此外，为了生成明确的堆栈，编译优化建议不要开，O0就好，最好再加上编译选项 -fno-omit-frame-pointer 这样能更好的显示出完整堆栈，定位起问题来会更加的轻松。