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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Building Highly Scalable Servers with Java NIO (O’Reilly)
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.
You can also try to build with Netty, a NIO client server framework. Events are like incoming a new connection, ready for read, ready for write, etc. Reactor Pattern The reactor pattern is one implementation technique of the event-driven architecture. I can run tens of thousands of threads on my desktop machine, but I’ve yet to see any problem where I could actually serve tens of thousands of connections from a single machine without everything crawling to a halt.
Mads Nielsen 3 After all, we can still revisit the status or results later. So that seems a weak argument to me. It is also the best MPM for isolating each request, so that a problem with a single request will not affect any other.
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. Some connections may be idle for tens of minutes at a servdr, but still open. It reads and parses the content in the request from the socket CPU bound.
Acceptor, selected when a new connection incomes. Processes are too heavyweight with slower context-switching and memory-consuming.
Building Highly Scalable Servers with Java NIO (O’Reilly) 
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.
A pool of threads poll the queue for incoming requests, and then process and respond. It is appropriate for sites that need to avoid threading for compatibility with non-thread-safe libraries.
Therefore, the thread-per-connection approach comes into being for better scalability, though programming with threads is error-prone and hard-to-debug.
Also NIO allows for ‘fair’ traffic delivery which is very important and very often overlooked as it bjild stable latency for the clients.
Actually, there are various ways to do this — different programming languages have their own jio e. Voo, I doubt you do have tens of thousands Runnable not just idling threads. You’re right I only tested bandwidth more important for my problems and I don’t think I’ve seen anything about latency so far.
In terms of processing the request, a threadpool is still used. However, the isolation and thread-safety come at a price. However, it retains much of the stability of a process-based server by keeping multiple processes available, each with many nip. Intuition told me it was manually done by the application developers with threads, but I was wrong.
Ben Voigt k 29 Unfortunately, there is always a one-to-one relationship between connections and threads. To handle web requests, there are two competitive web architectures — thread-based one and event-driven one. The reactor pattern is one implementation technique of the event-driven architecture. I’m reading about Channels in the JDK 7 docs here scalabe, and stumbled upon this:.