Let's see a small comparison between Imperative programming and Reactive programming: x = y + z.
In the preceding expression, assume y = 10 and z = 15. In this case, the x value would be 25. The value of x would be assigned at the time of the expression x = y + z. The value of x will never change after this expression.
This is perfectly alright in the traditional programming world. However, we might need a scenario where we should be able to follow up x when we change the value of y or z.
Our new scenario based values are:
- When y = 20 and z = 15, then x = 35
- When y = 20 and z = 25, then x = 45
The preceding scenario is not possible in Imperative programming, which we regularly use in our daily programming. But in some cases, we might need the value of x to be updated, corresponding to the change in y or z. Reactive programming is the perfect solution for this scenario. In Reactive programming, the value of x would automatically be updated, corresponding to the change in y or z.
Spreadsheet reference cells are the best example of Reactive programming. If a cell value changes, the referred cell value will be updated automatically. Another example can be found in a Model-View-Controller architecture, Reactive programming can automatically update the View, which is attached to the Model.
Reactive programming follows the Observer pattern to manipulate and transform the stream of data where the Publisher (observable) emits the items based on the Subscriber's need. As the Publisher emits the item, the Subscriber consumes those emitted items from the Publisher. Unlike the iterator pulling the items, here, the Publisher is pushing the items to the Subscriber.
As Reactive is a part of non-blocking architecture, it will be useful when we scale the application. Also, in non-blocking architecture, everything is considered as an event stream.
We will discuss more about Reactive in Java and Spring later in this chapter.
