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)
Mads Nielsen 3 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.
Once finished, the server writes the response to the client, and waits for the next request, or closes the connection.
Ben Voigt k 29 I’m reading about Channels in the JDK 7 docs hereand stumbled upon this:. A pool of threads poll the derver for incoming requests, and then process and respond.
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. Also NIO allows for ‘fair’ traffic delivery which is very important and very often overlooked as it ensures stable latency for the clients.
Associated handlers will be executed by the boss thread for specific events accept, read, write operations coming from those channels. In addition, hundreds or even thousands of concurrent sdalable can waste a great deal hpw stack space in the memory.
So that seems a weak argument to me. Acceptor, selected when a new connection incomes. 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) 
Connections exceeding the limitation of the queue will be dropped, but latencies for accepted connections become predictable. Also, scheduling thousands of threads is inefficient.
However, it retains much of the stability of a process-based server by keeping multiple processes available, each with many threads. In terms of processing the request, a threadpool is still used.
Understanding Reactor Pattern for Highly Scalable I/O Bound Web Server
The threads are doing some rather heavyweight work, so we reach the capacity of a single server before context switching overheads get a problem. Apache-MPM worker takes advantages of both processes and threads threadpool. As to C async programing with async and await keywords, that is another story. In this world, if you want your APIs to be popular, you have to make them async and non-blocking.
We mmultiplexed exhaust them!
It reads and parses the content in the request from the socket CPU bound. It is also the best MPM for isolating each request, so that a problem with a single request will not affect any other. Here is a simple implementation with a threadpool for connections: Some connections may be idle for tens of minutes at a time, but still open. That’s the usual argument, but: To handle web requests, there are two competitive web architectures — thread-based one and event-driven one. However, the isolation and thread-safety come at a price.
It is appropriate for sites that need to avoid threading for compatibility with non-thread-safe libraries. The answer may be as simple as just one single word — tradition. The dispatcher blocks on the socket for new connections and offers them to the bounded blocking queue. To answer these questions, let us first look at how an HTTP request is handled in general.
I’m reading about Channels in the JDK 7 docs hereand stumbled upon this: How to implement an echo web server with reactor pattern in Java?
The reactor pattern is one implementation technique of the event-driven architecture.