Hands-On Reactive Programming with Java 12

Don’t start writing a full reactive service from scratch if you are lacking practice. Start writing/refactoring non-reactive parts of an existing service. This is how we also approached various services with mixed reactive and non-reactive code with the goal to transition them to fully reactive. Check our recent Java project where we applied reactive programming.

Take a look at the sequences of events in real life in order to have a full understanding of the reactive programming Java paradigm. Any errors of the sub-components chained together are propagated downstream to be globally handled by the operator onErrorContinue . This ensures that the pipeline is kept running infinitely after handling the error. Having to care about error handling on the highest level fits perfectly to how we want our pipeline to behave. The flow is aborted at any point in the pipeline, except for consumeKafkaTopic() which has dedicated error handling on purpose.

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In Java, we write lambda expressions for Functional Programming. In reactive programming, we mostly use this lambda expression style. Let’s look at a traditional web application backend that was developed without using reactive programming. The HTTP response returned does not contain any data relevant for anything downstream in our pipeline.

That transformation operation will be applied to the item of Mono stream using the onNext() method that we discussed earlier. If there were no errors, the transformation will be applied to all the elements with the onComplete() method that we discussed earlier. If all the threads are occupied, the next requests that come into the server will have to wait until at least one thread frees up.

Upcoming events

It directly interacts with Java’s functional API, CompletableFuture, Stream, and Duration. We have definedUserRouterfor defining routes andUserHandlerto handle the request. In the upcoming lessons, you will see the main advantages of writing the code in a Reactive manner. Writing code with Callbacks is hard and difficult to read and maintain.

As a solution to the above drawbacks, a team of developers, led by Jonas Boner came together and introduced a new programming paradigm. Finally, we got all the bits and pieces crafted and can stick them together to one main flow. Reactor provides various operators that make this task very simple. The result is also very easy to read as it lists each of the stages of the flow depicted in the PushPipeline class.

Reactive Programming basics in Java

Furthermore, a single thread ensures that the upcoming batching of prices is not growing in memory complexity as this would be executed independently per thread. Note, that the Scheduler must be created only once, e.g. on initialization, to ensure usage of the same scheduler on every invocation of the Flux. Improved UX – due to the possibility to keep the application more responsive to its user.

We experimented with Schedulers using more than one thread as well. Our results showed no benefit over using a single thread for our use-case.

The Essence of Reactive Programming in Java

For instance, business logic is written imperative style, while event handling is performed by the RP. It means that you can write the code in an imperative paradigm but use a reactive one to perform certain functions. Well, it’s not just a technology fad — people jumping on the bandwagon with the shiny new toys. The driver is efficient resource utilization, or in other words, spending less money on servers and data centres. The promise of Reactive is that you can do more with less, specifically you can process higher loads with fewer threads. This is where the intersection of Reactive and non-blocking, asynchronous I/O comes to the foreground.

Before we dive into the topic of the article, let’s first look at the reason behind this popularity and how things were before reactive programming was introduced. It required a paradigm and mindset shift in how we craft and handle the flow of an application. This took some time for our team to learn the required techniques and implement them step-by-step in our large and evolving backend architecture.

Reactive Programming Tutorials

If you have a truly reactive framework to build on, then the answer is “you don’t care, you just declare the dependencies,” and that is really the power of a spreadsheet in a nutshell. It also highlights the difference between FRP and simple event-driven programming — it puts the “intelligent” in “intelligent routing”.

• Reactive Streams Specification is a set of rules or set of specifications that you need to follow when designing a reactive stream.
• But in a non-blocking and asynchronous way, the execution flow will not be blocked.
• In order to achieve this, trivago’s search backend engineering team had to develop a solution to serve available prices from our own platform to other hotel ads platforms.
• It’s generally accepted that events are “real-time” signals, meaning they’re generated contemporaneously with the condition they signal, and they must be processed in real time as well.
• If we use spring-boot, the webserver container will be tomcat and that container will have 200 maximum threads.

Project Reactor regroups multiple open source projects licensed under the Apache Software License 2. The main disadvantage of the Completable Future is that it does not handle well the async computations that return the collection of some data. Callbacks are asynchronous methods that accept a callback as a parameter and invoke it when the blocking call completes. In the example above, we have an application that receives the request from the client . In this Reactive Programming in Java tutorial, you will understand the need for Reactive programming in modern software development.

Microservices, CQRS, SAGA, Axon Framework.

In this case, the consumer can notify the producer to slow down the data publishing. It’s important to understand the meaning of reactive in order to understand the reactive programming paradigm. We react to events, this means reactive is a response to an event. In this way, we can define reactive programming as an event-driven method of programming. These allow us to build a fully reactive pipeline from start, i.e. reading the input data from a Kafka topic, to finish, i.e. sending the resulting HTTP requests to our target external hotel ads platform. Signaling between applications, particularly between what could be called “foreground” applications and “background,” or batch applications, that perform statistical analysis and database cleanup.

• The presumption in reactive programming is that there’s no control over the number or timing of the events, so the software must be resilient and highly scalable to manage variable loads.
• But this time, he waits until Bob comes and only after that he turns the movie on.
• The former recognizes important conditions or changes and generates messages to signal they’ve happened, and the latter deals with those messages appropriately.
• Since these can vary based on the hotelads platform, this part can be swapped out by application configuration.
• When it comes to huge volumes of data or multi-userness, we often need asynchronous processing to make our systems fast and responsive.
• IoT applications where sensors create events that then control real-world process steps, create business transactions or both.