Reactive Streams Tutorial
Introduction to Reactive Streams
Reactive Streams is a standard for asynchronous stream processing with non-blocking backpressure. It provides a way to handle streams of data in a more efficient and scalable manner. The main goal of Reactive Streams is to enable the construction of systems that can handle high volumes of data while avoiding resource exhaustion.
Key Concepts
Reactive Streams is based on four key interfaces:
- Publisher: Generates a stream of data.
- Subscriber: Consumes the stream of data.
- Subscription: Represents a one-to-one relationship between a Publisher and a Subscriber.
- Processor: A component that acts as both a Subscriber and a Publisher.
Creating a Simple Reactive Stream
To demonstrate how Reactive Streams work, let's create a simple example using Java. For this example, we will create a Publisher that emits a sequence of integers and a Subscriber that consumes them.
Example Code:
import org.reactivestreams.Subscriber;
import org.reactivestreams.Subscription;
public class SimpleReactiveStream {
public static void main(String[] args) {
Publisher
subscriber.onSubscribe(new Subscription() {
public void request(long n) {
for (int i = 0; i < n; i++) {
subscriber.onNext(i);
}
subscriber.onComplete();
}
});
};
Subscriber
public void onSubscribe(Subscription subscription) {
subscription.request(5);
}
public void onNext(Integer item) {
System.out.println("Received: " + item);
}
public void onError(Throwable throwable) {
throwable.printStackTrace();
}
public void onComplete() {
System.out.println("Done!");
}
};
publisher.subscribe(subscriber);
}
}
Output:
Received: 0
Received: 1
Received: 2
Received: 3
Received: 4
Done!
Backpressure in Reactive Streams
One of the essential features of Reactive Streams is backpressure. This mechanism allows a Subscriber to control the flow of data from a Publisher, preventing the Subscriber from being overwhelmed by too much data at once. The Subscriber can request a specific number of items, thus allowing for better resource management.
In the previous example, the Subscriber requested five items from the Publisher. If it had requested a larger number of items, the Publisher would have been required to pause until the Subscriber processed the items it had already received.
Conclusion
Reactive Streams provide a powerful way to handle asynchronous data streams in a non-blocking way. By implementing a standard for backpressure, Reactive Streams enable developers to create systems that can scale efficiently and handle high volumes of data without running into resource exhaustion. This tutorial introduced you to the fundamental concepts and a basic example of how to use Reactive Streams.