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 [26].

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In this world, if you want your APIs to be popular, you have to make them async and non-blocking.

Associated handlers will be executed by the boss thread for specific events accept, read, write operations coming from those channels. Also NIO allows for ‘fair’ traffic delivery which is very important and very often overlooked as it ensures stable latency for the clients.

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Its concurrency model is based on an event loop. 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. Sign up or log in Sign up using Google.

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.


The reactor pattern is one implementation technique of the event-driven architecture. Think about switching electric current vs. References C10k problem, http: Here is a simple implementation with a threadpool for connections: How to implement an echo web server with reactor pattern in Java?

JavaScript has a tradition of being single threaded scalab,e it has limited web worker API. Therefore, the thread-per-connection approach comes into being for ho scalability, though programming with threads is error-prone and hard-to-debug. Events are like incoming a new connection, ready for read, ready for write, etc.

As to C async programing with async and await keywords, that is another story. Then the request is dispatched to the application level for domain-specific logics, which would probably visit the file system for data.

Nowadays Apache-MPM prefork still retains the feature for the following reasons. Once finished, the server writes the response to the client, and waits for the next request, or closes the connection. Stack Overflow works best with JavaScript enabled. Bad news for us!

Processes are too heavyweight with slower context-switching and memory-consuming. You can also try to build with Netty, a NIO client server framework. Talk is cheap and show me the code: Mads Nielsen 3 So that seems a weak argument to me. 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. It is also the best MPM for isolating each request, so that a problem with a single request will not affect any other.

That’s the usual argument, but: Actually, there are various ways to do this — different programming languages have their own libraries e. It looks quite straightforward in JavaScript as shown above, but how is it implemented under the hood? Sign up using Facebook. Unfortunately, there is always a one-to-one relationship between connections and threads. Post as a guest Name. To answer these questions, let us first look at how an HTTP request is handled in general.


Email Required, but never shown. That said, the point of Channel is to make this less tricky. The dispatcher blocks on the socket for new connections and offers them niio the bounded blocking queue. Connections exceeding the limitation of the queue will be dropped, but latencies for accepted connections become predictable.

Building Highly Scalable Servers with Java NIO (O’Reilly) []

Ben Voigt k 29 In terms of processing the request, a threadpool is still used. Intuition told me it was manually done by the application developers with threads, but I was wrong.

Voo, I doubt you do have tens of thousands Runnable not just idling threads. 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.

It reads and parses the content in the request from the socket CPU bound.