I’ve already talked a bit about data parallelism, but in this chapter I’m going to cover how we can use lambda expressions to write concurrent applications that efficiently perform message passing and nonblocking I/O.
Some of the examples in this chapter are written using the Vert.x and RxJava frameworks. The principles are more general, though, and can be used in other frameworks and in your own code without you necessarily needing frameworks at all.
When I introduced parallelism, I talked a lot about trying to use a lot of cores efficiently. That approach is really helpful, but when trying to process a lot of data, it’s not the only threading model that you might want to use.
Let’s suppose you’re trying to write a chat service that handles a very high number of users. Every time a user connects to your service, a TCP connection to your server is opened. If you follow a traditional threading model, every time you want to write some data to your user, you would call a method that sends the user the data. This method call would block the thread that you’re running on.
This approach to I/O, called blocking I/O, is fairly common and fairly easy to understand because the interaction with users follows a normal sequential flow of control through your program. The downside is that when you start looking at scaling your system to a significant number of users, you need to start a significant number of threads on your server in order ...