Building Highly Scalable Servers with Java NIO (4 messages) Developing a fully functional router based on I/O multiplexing was not simple. : Building Highly Scalable Servers with Java NIO multiplexing is significantly harder to understand and to implement correctly. use the NIO API (ByteBu ers, non-blocking I/O) The classical I/O API is very easy Java NIO Framework was started after Ron Hitchen’s presentation How to Build a Scalable Multiplexed Server With NIO at the JavaOne Conference .
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Understanding Reactor Pattern for Highly Scalable I/O Bound Web Server
Then the request is dispatched to the application level for domain-specific logics, which would probably visit the file system for data. Once finished, the server writes the response to the client, and waits for the next request, or closes the connection.
Think about switching electric current vs.
Intuition told multiplexef it was manually done by the application developers with threads, but I was wrong. Actually, there are various ways to do this — different programming languages have their own libraries e. And the operating systems themselves also provide system calls in the kernel level — e. To handle web requests, there are two competitive web architectures — thread-based one and event-driven one.
Nowadays Apache-MPM prefork still retains the feature for the following reasons. It is appropriate for sites that need to avoid threading for compatibility with non-thread-safe libraries.
It is also the best MPM for isolating each request, so that a problem with a single request will not affect any other. However, the isolation and thread-safety come at a price. Processes are too heavyweight with slower context-switching and memory-consuming. Therefore, the thread-per-connection approach comes into being for better scalability, though programming with threads is error-prone and hard-to-debug. The dispatcher blocks on the socket for new connections and offers them to the bounded blocking queue.
Connections exceeding the limitation of the queue will be dropped, but latencies for accepted connections become predictable.
A pool of threads poll the queue for incoming requests, and then process and respond. Apache-MPM worker takes advantages of both processes and threads threadpool. By using threads to serve requests, it is able to serve a large number of requests with fewer system resources than a process-based server.
Building Highly Scalable Servers with Java NIO (O’Reilly) 
However, it retains much of the stability of a process-based server by keeping multiple processes available, each with many threads. Unfortunately, there is always a one-to-one relationship between connections and threads. Long-living connections like Keep-Alive connections give rise to a large number of worker threads waiting in the idle state for whatever it is slow, e.
In addition, hundreds or even thousands of concurrent threads can setver a great deal of stack space in the memory. The reactor pattern is one implementation technique of the event-driven architecture. Events are like incoming a new connection, ready for read, ready for write, etc. Talk is cheap and show me the code: You can also try to build with Netty, a NIO client server framework.
In the following code, a single boss thread is in an event loop blocking on a selector, which is registered with several channels and handlers.
Building Highly Scalable Servers with Java NIO (O’Reilly)
As wihh C async programing with async and await keywords, that is another story.
Here is a simple implementation with a threadpool for connections: Reactor Pattern The reactor pattern is one implementation technique of the event-driven architecture. This pattern decouples modular application-level code from reusable reactor implementation. Acceptor, selected when a new connection incomes.
References C10k problem, http: