msgpack[C++]使用笔记 和 msgpack/cPickle性能对比
python版本msgpack安装：
wget http://pypi.python.org/packages/source/m/msgpack-python/msgpack-python-0.1.9.tar.gz
python2.x setup.py install --prefix=/usr/local/similarlib/
python版本的msgpack灰常好用，速度上比python内置的pickle和cpickle都要快一些，C++版本的使用比较麻烦，下面是本人学习时的一个demo，解析python-msgpack dump的一个复杂字典。
- #include <msgpack.hpp>
- #include <fstream>
- #include <iostream>
- using namespace std;
- template <class T>
- void msgunpack(const char* binary_file, T& t, char* buff, uint32_t max){
- msgpack::unpacked msg;
- ifstream tf_file(binary_file,ios::in|ios::binary|ios::ate);
- uint32_t size = tf_file.tellg();
- tf_file.seekg(0, ios::beg);
- tf_file.read(buff, size);
- tf_file.close();
- msgpack::unpack(&msg, buff, size);
- msg.get().convert(&t);
- }
- typedef map<uint32_t, uint32_t> WordsMap;
- typedef map<uint32_t, WordsMap> FieldsMap;
- typedef map<uint64_t, FieldsMap> DocsMap;
- int main(int argc, char** argv)
- {
- uint32_t MAX_BUFF = 1024*1024*100; //100MB
- char* BUFF = new char[MAX_BUFF];
- DocsMap docsMap;
- msgpack::unpacked msg;
- msgunpack("/data/wikidoc/tf_dict_for_nodes/1-1000", docsMap, BUFF, MAX_BUFF);
- // msg.get().convert(&docsMap);
- cout << docsMap.size() << endl;
- delete[] BUFF;
- }
下面是本人自己封装的一个msgpack接口头文件mymsgpack.h
- #ifndef MY_MSGPACK_H
- #ifndef MY_MSGPACK_H
- #define MY_MSGPACK_H
- #include <fstream>
- #include <msgpack.hpp>
- using namespace std;
- template <class T>
- void load_from_file(const char* binary_file, T& t) {
- ifstream binaryFstream(binary_file,ios::in|ios::binary|ios::ate);
- uint32_t size = binaryFstream.tellg();
- char* buff = new char[size];
- binaryFstream.seekg(0, ios::beg);
- binaryFstream.read(buff, size);
- binaryFstream.close();
- msgpack::unpacked msg;
- msgpack::unpack(&msg, buff, size);
- msg.get().convert(&t);
- delete[] buff;
- }
- template <class T>
- void load_from_str(const char* binary_str, int len, T& t) {
- msgpack::unpacked msg;
- msgpack::unpack(&msg, binary_str, len);
- msg.get().convert(&t);
- }
- template <class T>
- void dump_to_file(T& t, const char* dump_file) {
- msgpack::sbuffer sbuf;
- msgpack::pack(sbuf, t);
- ofstream dumpFstream(dump_file, ios::out|ios::binary|ios::trunc);
- dumpFstream.write(sbuf.data(), sbuf.size());
- dumpFstream.close();
- }
- template <class T>
- void dump_to_str(T& t, char** dump_str, int& len) { //外部释放*dump_str
- msgpack::sbuffer sbuf;
- msgpack::pack(sbuf, t);
- len = sbuf.size();
- *dump_str = (char*)malloc(sbuf.size());
- memcpy(*dump_str, sbuf.data(), sbuf.size());
- }
- #endif
msgpack编译通过，链接不上的问题 undefined reference to `__sync_sub_and_fetch_4'
在x84_64机器上正常，在32bit机器上出现上述问题
- [xudongsong@BigServerU-4 msgpack-0.5.7]$ cat /etc/issue
- CentOS release 5.4 (Final)
- Kernel \r on an \m
- [xudongsong@BigServerU-4 msgpack-0.5.7]$ file /sbin/init
- /sbin/init: ELF 32-bit LSB executable, Intel 80386, version 1 (SYSV), for GNU/Linux 2.6.9, dynamically linked (uses shared libs), for GNU/Linux 2.6.9, stripped
./configure不报错，但是查看config.log显示有错误，程序链接msgpack的库时也报错
原因：gcc不能识别CPU体系，需要手动指明
- [xudongsong@BigServerU-4 msgpack-0.5.7]$ CFLAGS="-march=pentium -mtune=pentium" ./configure --prefix=/home/xudongsong/msgpack_static --enable-static=yes --enable-shared=no
make, make install
[xudongsong@BigServerU-4 jobs]$ g++ job_calc_weight.cpp -o job_calc_weight -I/home/xudongsong/msgpack_static/include/ -L/home/xudongsong/msgpack_static/lib/ -lmsgpack
通过！
下面是msgpack和cPickle进行性能pk的demo程序（不比较pickle，是因为它比cPickle更慢，《Python cook book》里面有说明）：
- mport sys,time,msgpack,pickle,cPickle,random
- test_list = []
- i = 0
- while i<100000:
- test_list = random.randrange(1,100000)
- i += 1
- print "common len(serialize) = %s"%len(cPickle.dumps(test_list,0))
- print "compress len(serialize) = %s"%len(cPickle.dumps(test_list,1))
- #------------------------------------------------------------------------
- results = {}
- time_start = time.time()
- for i in range(1,1000000):
- results[i] = cPickle.dumps(test_list,1)
- time_mid_1 = time.time()
- print "cPickle dumps eats %s s"%str(time_mid_1-time_start)
- for i in range(1,1000000):
- cPickle.loads(results[i])
- time_mid_2 = time.time()
- print "cPickle loads eats %s s"%str(time_mid_2-time_mid_1)
- #------------------------------------------------------------------------
- results = {}
- time_start = time.time()
- for i in range(1,1000000):
- results[i] = msgpack.dumps(test_list)
- time_mid_1 = time.time()
- print "msgpack pack eats %s s"%str(time_mid_1-time_start)
- for i in range(1,1000000):
- msgpack.loads(results[i])
- time_mid_2 = time.time()
- print "msgpack unpack eats %s s"%str(time_mid_2-time_mid_1)
