On the lookout for some top-end mobile application development company in USA? Up with the vogue to create a brand new mobile app? There has been a lot of buzz about reactive systems over the past couple of years. Along with the buzz comes the collection of relevant keyword salads like reactive streams, reactive extensions, reactive programming, functional reactive programming, etc. If you've been in the technology industry long enough, you've seen the cyclical ups and downs of buzzwords and acronyms from time to time.
So, if you are quite intrigued towards knowing what reactive systems actually are, this blog post is going to come to your help in more than one way. It’s going to describe the essential characteristics of the reactive systems: responsive, resilient, elastic and message-driven. That gives a high-level picture and sounds a little generic. In particular, responsiveness, resilience, elasticity described in the manifesto are almost standard requirements of many real-world applications these days. Perhaps "message-driven" is the requirement that truly differentiates reactive systems from others. Under the hood, a reactive system relies on interactions via allochronic message-passing that establishes boundaries among individual components. Such an interaction model helps in paving the path towards loose-coupling both time-wise and location-wise for concurrency and distributability, respectively. In addition, it allows the system to be integrally equipped with some non-blocking mechanism to regulate data flows.
Adhering to reactive programming has now become a trend today. This blog would now discuss certain benefits of going reactive.
Understanding the difference between observables is the key to successfully use reactive programming. There are two classes of streams: hot and cold. And, at this point, one tries to see what are the different streams one is going to deal with in his/her program. Cold observables are lazy. They don’t do anything until someone starts observing them. They only start running when they are consumed. Cold streams are used to represent asynchronous actions, for example, that it won’t be executed until someone is interested in the result. Another example would be a file download. It won’t start pulling the bytes if no one is going to do something with the data. The data produced by a cold stream is not shared among subscribers and when you subscribe you get all the items.
Hot streams are active before the subscription like a stock ticker, or data sent by a sensor or a user. The data is independent of an individual subscriber. When an observer subscribes to a hot observable, it will get all values in the stream that are emitted after it subscribes. The values are shared among all subscribers. For example, even if no one has subscribed to a thermometer, it measures and publishes the current temperature. When a subscriber registers to the stream, it automatically receives the next measure. So, why it’s so important to understand whether your streams are hot or cold? Because it changes how your code consumes the conveyed items. If you are not subscribed to a hot observable, you won’t receive the data, and this data is lost.
Also, when using reactive programming, data streams are going to be the spine of your application. Events, messages, calls, and even failures are going to be conveyed by a data stream. With reactive programming, you observe these streams and react when a value is emitted. So, in your code, you are going to create data streams of anything and from anything: click events, HTTP requests, consumed messages, availability notifications, changes on a variable, cache events, measures from a sensor, literally anything that may change or happen. This has an intriguing side-effect on your application: it’s becoming inherently asynchronous.
Using reactive programming does not build a reactive system. Reactive systems are an architectural style to build responsive distributed systems. Reactive Systems could be seen as distributed systems done right. A reactive system is characterized by four properties:
Despite the simplicity of these fundamental principles of reactive systems, building one of them is tricky. Reactive Programming and Reactive eXtension provides a development model to tame the asynchronous beast. By using it wisely, your code is going to stay readable, and understandable. However, using reactive programming does not transform your system into a Reactive System. Reactive Systems are the next level.
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