如何在更多线程上运行提升 asio 解析器服务

如文档中所述，Boost.Asio 将为每个io_service创建一个额外的线程，以模拟第一次调用 resolver::async_resolve() 时的异步主机解析。

仅当在与不同io_service关联的resolver上启动异步解析操作时，创建多个io_service对象才允许并发主机解析。 例如，以下代码不会执行并发主机解析，因为两个解析程序使用相同的服务：

boost::asio::io_service service1;
boost::asio::ip::udp::resolver resolver1(service1); // using service1
boost::asio::ip::udp::resolver resolver2(service1); // using service1
resolver1.async_resolve(...); 
resolver2.async_resolve(...);

另一方面，以下内容将执行并发主机解析，因为每个解析程序使用不同的服务：

boost::asio::io_service service1;
boost::asio::io_service service2;
boost::asio::ip::udp::resolver resolver1(service1); // using service1
boost::asio::ip::udp::resolver resolver2(service2); // using service2
resolver1.async_resolve(...); 
resolver2.async_resolve(...);

假设每io_service resolver，为了获得并发性，应用程序负责将解析操作分派给不同的解析器。 一个简单的工作分配策略（如循环）可能就足够了。

另一方面，可以将此责任委托给io_service，允许它以类似于Boost.Asio内部执行的方式分发模拟异步主机分辨率的工作。 同步 resolver::resolve() 成员函数在调用线程中执行工作。 因此，应用程序可以创建由线程池提供服务的io_service。 当需要异步主机解析时，会将作业发布到io_service中，该作业将创建创建resolver并执行同步解析，并使用结果调用用户处理程序。 下面是一个完整的基本示例，其中 resolver 类使用线程池模拟异步主机解析：

#include <iostream>
#include <boost/asio.hpp>
#include <boost/bind.hpp>
#include <boost/optional.hpp>
#include <boost/thread.hpp>
/// @brief Type used to emulate asynchronous host resolution with a 
///        dedicated thread pool.
class resolver
{
public:
  resolver(const std::size_t pool_size)
    : work_(boost::ref(io_service_))
  {
    // Create pool.
    for (std::size_t i = 0; i < pool_size; ++i)
      threads_.create_thread(
        boost::bind(&boost::asio::io_service::run, &io_service_));
  }
  ~resolver()
  {
    work_ = boost::none;
    threads_.join_all();
  }
  template <typename QueryOrEndpoint, typename Handler>
  void async_resolve(QueryOrEndpoint query, Handler handler)
  {
    io_service_.post(boost::bind(
        &resolver::do_async_resolve<QueryOrEndpoint, Handler>, this,
        query, handler));
  }
private:
  /// @brief Resolve address and invoke continuation handler.
  template <typename QueryOrEndpoint, typename Handler>
  void do_async_resolve(const QueryOrEndpoint& query, Handler handler)
  {
    typedef typename QueryOrEndpoint::protocol_type protocol_type;
    typedef typename protocol_type::resolver        resolver_type;
    // Resolve synchronously, as synchronous resolution will perform work
    // in the calling thread.  Thus, it will not use Boost.Asio's internal
    // thread that is used for asynchronous resolution.
    boost::system::error_code error;
    resolver_type resolver(io_service_);
    typename resolver_type::iterator result = resolver.resolve(query, error);
    // Invoke user handler.
    handler(error, result);
  }
private:
  boost::asio::io_service io_service_;
  boost::optional<boost::asio::io_service::work> work_;
  boost::thread_group threads_;
};
template <typename ProtocolType>
void handle_resolve(
    const boost::system::error_code& error,
    typename ProtocolType::resolver::iterator iterator)
{
  std::stringstream stream;
  stream << "handle_resolve:n"
            "  " << error.message() << "n";
  if (!error)
    stream << "  " << iterator->endpoint() << "n";
  std::cout << stream.str();
  std::cout.flush();
}
int main()
{
  // Resolver will emulate asynchronous host resolution with a pool of 5
  // threads.
  resolver resolver(5);
  namespace ip = boost::asio::ip;
  resolver.async_resolve( 
      ip::udp::resolver::query("localhost", "12345"),
      &handle_resolve<ip::udp>);
  resolver.async_resolve(
      ip::tcp::resolver::query("www.google.com", "80"),
      &handle_resolve<ip::tcp>);
  resolver.async_resolve(
      ip::udp::resolver::query("www.stackoverflow.com", "80"),
      &handle_resolve<ip::udp>);
  resolver.async_resolve(
      ip::icmp::resolver::query("some.other.address", "54321"),
      &handle_resolve<ip::icmp>);
}

和带注释的输出：

handle_resolve:
  Success
  127.0.0.1:12345   // localhost
handle_resolve:
  Service not found // bogus
handle_resolve:
  Success
  173.194.77.147:80 // google
handle_resolve:
  Success
  198.252.206.16:80 // stackoverflow

的是两个io_service ioService，因为每个都由一个线程运行。我的意思是你通过调用io_service::run来阻止线程的正常执行。

我认为代码本身是正确的。