Reactive Programming Advantages/Disadvantages
I keep studying and trying Reactive Style of coding using Reactor and RxJava. I do understand that reactive coding makes better utilization of CPU compared to single threaded execution.
Is there any concrete comparison between reactive programming vs imperative programming in web based applications?
How much is the performance gain, throughput I achieve by using reactive programming over non-reactive programming?
Also what are the advantages and disadvantages of Reactive Programming?
Is there any statistical benchmark?
Well, Reactive Programming means you are doing all your IO bound tasks such as network calls asynchronously. For an instance say your application calls an external REST API or a database, you can do that invocation asynchronously. If you do so your current thread does not block. You can serve lots of requests by merely spawning one or few threads. If you follow blocking approach you need to have one thread to handle each and every request. You may refer my multi part blog post part one, part two and part three for further details.
Other than that you may use callbacks to do the same. You can do asynchronous invocation using callbacks. But if you do so sometimes you may ended up with callback hell. Having one callback inside another leads to very complex codes which are very hard to maintain. On the other hand RxJava lends you write asynchronous code which is much more simple, composable and readable. Also RxJava provides you a lots of powerful operators such as Map, Zip etc which makes your code much more simple while boosting the performance due to parallel executions of different tasks which are not dependent on each other.
RxJava is not another Observer implementation with set of operators rather it gives you good error handling and retry mechanisms which are really handy.
But I have not conducted any bench marking of RxJava with imperative programming approach to commend you statistically. But I am pretty much sure RxJava should yield good performance over blocking mechanisms.
Update
Since I gathered more experience over time, I thought of adding more points to my answer.
Based on the article, ReactiveX is a library for composing asynchronous and event-based programs by using observable sequences. I reckon you to go through this introductory article in the first place.
These are some properties of reactive systems: Event Driven, Scalable, Resilient, Responsive
When it comes to RxJava it offers two main facilities to a programmer. First it offers a nice composable API using a rich set of operators such as zip, concat, map etc. This yields more simple and readable code. When it comes to code, readability and simplicity are the uttermost important properties. Second, it provides excellent abstractions, that enable concurrency to become declarative.
A popular misconception is that Rx is multithreaded by default. In fact, Rx is single-threaded by default. If you want to do things asynchronously, then you have to tell it explicitly using subscribeOn and observeOn operators by passing relevant schedulers. RxJava gives you thread pools to do asynchronous tasks. There are many schedulers such as IO, Computation and so forth. IO scheduler as the name suggests is best suited for IO intensive tasks such as network calls etc. on the contrary, Computation scheduler is good for more CPU intensive computation tasks. You can also hook up your own Executor services with RxJava too. The built in schedulers mainly helps you to get rid of maintaining your own Executor services, making your code more simple.
Finally a word on subscribeOn and observeOn
In the Rx world, there are generally two things you want to control the concurrency model for:
- The invocation of the subscription
- The observing of notifications
SubscribeOn: specify the Scheduler on which an Observable will operate.
ObserveOn: specify the Scheduler on which an observer will observe this Observable
Disadvantages
- More memory intensive to store streams of data most of the times (since it is based on streams over time).
- Might feel unconventional to learn at start(needs everything to be a stream).
- Most complexities have to be dealt with at the time of declaration of new services.
Lack of good and simple resources to learn.
Often confused to be equivalent to Functional Reactive Programming.
Apart of what is already mentioned in other responses regarding no blocking features, another great feature about reactive programing is the important use of backpressure. Normally it is used in situations where your publisher emits more information than your consumer can process.
So having this mechanism you can control the flow of traffic between both and avoid nasty out of memory problems.
You can see some practical examples of reactive programming here: https://github.com/politrons/reactive
And about back pressure here: https://github.com/politrons/Akka/blob/master/src/main/scala/stream/BackPressure.scala
By the way, the only disadvantage about reactive programming, is the learning curve because you're changing the programming paradigm. But nowadays all important companies respect and follow the reactive manifesto.