zeroMQ编程实例

1、安装zeroMQ

wget http://download.zeromq.org/zeromq-4.1.2.tar.gztar -xvzf zeromq-4.1.2.tar.gzcd zeromq-4.1.2.tar.gz./configure --without-securitymake && make install

或者：

git clone https://github.com/zeromq/libzmq.git

如果使用c++语言编程还需要获取到

zeroMQ的c++版头文件

git clone https://github.com/zeromq/cppzmq.git

将zmq.hpp拷贝到/use/local/include下

2、三种模式实例

    1、请求回应简单模式：

    server.cpp

////  Hello World server in C++//  Binds REP socket to tcp://*:5555//  Expects "Hello" from client, replies with "World"//#include <zmq.hpp>#include <string>#include <iostream>#ifndef _WIN32#include <unistd.h>#else#include <windows.h>#define sleep(n)    Sleep(n)#endif#include <sys/time.h>int main () {    //  Prepare our context and socket    zmq::context_t context (1);    zmq::socket_t socket (context, ZMQ_REP);    socket.bind ("tcp://*:5555");    struct timespec tv = {1,0};    while (true) {        zmq::message_t request;        //  Wait for next request from client        socket.recv (&request);        std::cout << "Received Hello" << std::endl;        //  Do some 'work'// sleep(1);if(nanosleep(&tv, NULL) == -1){exit(-1);}        //  Send reply back to client        zmq::message_t reply (5);        memcpy ((void *) reply.data (), "World", 5);        socket.send (reply);    }    return 0;}

client.cpp

#include <zmq.hpp>#include <string>#include <iostream>int main (){    //  Prepare our context and socket    zmq::context_t context (1);    zmq::socket_t socket (context, ZMQ_REQ);    std::cout << "Connecting to hello world server…" << std::endl;    socket.connect ("tcp://localhost:5555");    //  Do 10 requests, waiting each time for a response    for (int request_nbr = 0; request_nbr != 10; request_nbr++) {        zmq::message_t request (6);        memcpy ((void *) request.data (), "Hello", 5);        std::cout << "Sending Hello " << request_nbr << "…" << std::endl;        socket.send (request);        //  Get the reply.        zmq::message_t reply;        socket.recv (&reply);        std::cout << "Received World " << request_nbr << std::endl;    }    return 0;}

g++ -o server server.cpp -lzmq

g++ -o client client.cpp -lzmq

2、发布订阅模式：

server.cpp

#include <zmq.hpp>#include <stdio.h>#include <stdlib.h>#include <time.h>#define within(num) (int) ((float) num * random () / (RAND_MAX + 1.0))int main () {    //  Prepare our context and publisher    zmq::context_t context (1);    zmq::socket_t publisher (context, ZMQ_PUB);    publisher.bind("tcp://*:5556");     //  Initialize random number generator    srandom ((unsigned) time (NULL));    while (1) {        int zipcode, temperature, relhumidity;        //  Get values that will fool the boss        zipcode     = within (100000);        temperature = within (215) - 80;        relhumidity = within (50) + 10;        //  Send message to all subscribers        zmq::message_t message(20);        snprintf ((char *) message.data(), 20 ,  "%05d %d %d", zipcode, temperature, relhumidity);        publisher.send(message);    }    return 0;}

client.cpp

#include <zmq.hpp>#include <iostream>#include <sstream>int main (int argc, char *argv[]){    zmq::context_t context (1);    //  Socket to talk to server    std::cout << "Collecting updates from weather server…\n" << std::endl;    zmq::socket_t subscriber (context, ZMQ_SUB);    subscriber.connect("tcp://localhost:5556");    //  Subscribe to zipcode, default is NYC, 10001    const char *filter = (argc > 1)? argv [1]: "10001 ";    subscriber.setsockopt(ZMQ_SUBSCRIBE, filter, strlen (filter));    //  Process 100 updates    int update_nbr;    long total_temp = 0;do{for (update_nbr = 0; update_nbr < 100; update_nbr++) {zmq::message_t update;int zipcode, temperature, relhumidity;subscriber.recv(&update);std::istringstream iss(static_cast<char*>(update.data()));iss >> zipcode >> temperature >> relhumidity ;total_temp += temperature;}std::cout     << "Average temperature for zipcode '"<< filter  <<"' was "<<(int) (total_temp / update_nbr) <<"F"  << std::endl;sleep(1);} while (1);     return 0;}

3、管道模式：

taskvent: Parallel task ventilator in c++

////  Task ventilator in C++//  Binds PUSH socket to tcp://localhost:5557//  Sends batch of tasks to workers via that socket////  Olivier Chamoux <[e-mail]>//#include <zmq.hpp>#include <stdlib.h>#include <stdio.h>#include <unistd.h>#include <iostream>#define within(num) (int) ((float) num * random () / (RAND_MAX + 1.0))int main (int argc, char *argv[]){    zmq::context_t context (1);    //  Socket to send messages on    zmq::socket_t  sender(context, ZMQ_PUSH);    sender.bind("tcp://*:5557");    std::cout << "Press Enter when the workers are ready: " << std::endl;    getchar ();    std::cout << "Sending tasks to workers…\n" << std::endl;    //  The first message is "0" and signals start of batch    zmq::socket_t sink(context, ZMQ_PUSH);    sink.connect("tcp://localhost:5558");    zmq::message_t message(2);    memcpy(message.data(), "0", 1);    sink.send(message);    //  Initialize random number generator    srandom ((unsigned) time (NULL));    //  Send 100 tasks    int task_nbr;    int total_msec = 0;     //  Total expected cost in msecs    for (task_nbr = 0; task_nbr < 100; task_nbr++) {        int workload;        //  Random workload from 1 to 100msecs        workload = within (100) + 1;        total_msec += workload;        message.rebuild(10);        sprintf ((char *) message.data(), "%d", workload);        sender.send(message);    }    std::cout << "Total expected cost: " << total_msec << " msec" << std::endl;    sleep (1);              //  Give 0MQ time to deliver    return 0;}

taskwork: Parallel task worker in C++

////  Task worker in C++//  Connects PULL socket to tcp://localhost:5557//  Collects workloads from ventilator via that socket//  Connects PUSH socket to tcp://localhost:5558//  Sends results to sink via that socket////  Olivier Chamoux <[e-mail]>//#include "zhelpers.hpp"int main (int argc, char *argv[]){    zmq::context_t context(1);    //  Socket to receive messages on    zmq::socket_t receiver(context, ZMQ_PULL);    receiver.connect("tcp://localhost:5557");    //  Socket to send messages to    zmq::socket_t sender(context, ZMQ_PUSH);    sender.connect("tcp://localhost:5558");    //  Process tasks forever    while (1) {        zmq::message_t message;        int workload;           //  Workload in msecs        receiver.recv(&message);        std::istringstream iss(static_cast<char*>(message.data()));        iss >> workload;        //  Do the work        s_sleep(workload);        //  Send results to sink        message.rebuild();        sender.send(message);        //  Simple progress indicator for the viewer        std::cout << "." << std::flush;    }    return 0;}

tasksink: Parallel task sink in C++

////  Task sink in C++//  Binds PULL socket to tcp://localhost:5558//  Collects results from workers via that socket////  Olivier Chamoux <[e-mail]>//#include <zmq.hpp>#include <time.h>#include <sys/time.h>#include <iostream>int main (int argc, char *argv[]){    //  Prepare our context and socket    zmq::context_t context(1);    zmq::socket_t receiver(context,ZMQ_PULL);    receiver.bind("tcp://*:5558");    //  Wait for start of batch    zmq::message_t message;    receiver.recv(&message);    //  Start our clock now    struct timeval tstart;    gettimeofday (&tstart, NULL);    //  Process 100 confirmations    int task_nbr;    int total_msec = 0;     //  Total calculated cost in msecs    for (task_nbr = 0; task_nbr < 100; task_nbr++) {        receiver.recv(&message);        if ((task_nbr / 10) * 10 == task_nbr)            std::cout << ":" << std::flush;        else            std::cout << "." << std::flush;    }    //  Calculate and report duration of batch    struct timeval tend, tdiff;    gettimeofday (&tend, NULL);    if (tend.tv_usec < tstart.tv_usec) {        tdiff.tv_sec = tend.tv_sec - tstart.tv_sec - 1;        tdiff.tv_usec = 1000000 + tend.tv_usec - tstart.tv_usec;    }    else {        tdiff.tv_sec = tend.tv_sec - tstart.tv_sec;        tdiff.tv_usec = tend.tv_usec - tstart.tv_usec;    }    total_msec = tdiff.tv_sec * 1000 + tdiff.tv_usec / 1000;    std::cout << "\nTotal elapsed time: " << total_msec << " msec\n" << std::endl;    return 0;}

zeroMQ在设计上主要采用了以下几个高性能的特征：

1、无锁的队列模型

      对于跨线程间的交互（用户端和session）之间的数据交换通道pipe，采用无锁的队列算法CAS；在pipe的两端注册有异步事件，在读或者写消息到pipe的时，会自动触发读写事件。

2、批量处理的算法

     对于传统的消息处理，每个消息在发送和接收的时候，都需要系统的调用，这样对于大量的消息，系统的开销比较大，zeroMQ对于批量的消息，进行了适应性的优化，可以批量的接收和发送消息。

3、多核下的线程绑定，无须CPU切换

    区别于传统的多线程并发模式，信号量或者临界区， zeroMQ充分利用多核的优势，每个核绑定运行一个工作者线程，避免多线程之间的CPU切换开销。

文章参考：

http://github.tiankonguse.com/blog/2014/12/20/zoermq-study/

http://zguide.zeromq.org/page:all

http://blog.csdn.net/sunrise918/article/details/8701274