Get ready to experience fast and scalable performance in your web applications as we dive into the world of Reactive Programming. Our guide using WebFlux is perfect for both beginners and experts a like.
Reactive programming by spring webflux - DN Scrum Breakfast - Nov 2018Scrum Breakfast Vietnam
Are you struggling to create a non-blocking REST application or a reactive micro-services? Spring WebFlux, a new module introduced by Spring 5 may help.
This new module introduces:
- Fully non-blocking
- Supports Reactive Streams back pressure
- Runs on such servers as Netty, Undertow, and Servlet 3.1+ containers
- Its support for the reactive programming model
In our next Scrum Breakfast, we will discuss Spring WebFlux, its benefit and how we implement it.
Our workshop will be including the following:
- What is reactive programming
- Introduction to Spring Webflux
- Tea break
- The details in Spring Webflux
- Reactive stack demonstration
- Q&A
This document provides an overview of reactive programming in Java and Spring 5. It discusses reactive programming concepts like reactive streams specification, Reactor library, and operators. It also covers how to build reactive applications with Spring WebFlux, including creating reactive controllers, routing with functional endpoints, using WebClient for HTTP requests, and testing with WebTestClient.
This is the document I created when I made the presentation for Eonics on Hack Night 21. Make sure to watch the document for a bit of history about Reactive programming.
The project has since moved to GitHub on https://github.com/jesperancinha/kitten-house-care-parent.
It has now been converted to Kotlin and the test branches are no longer available. If you have any questions, please post them on GitHub, or alternative post in the community on my channel jesprotech on YouTube.
This document provides an overview of reactive programming and how it can be applied to Java applications using frameworks like Project Reactor and Spring WebFlux. It defines reactive programming as composing asynchronous and event-based streams using non-blocking operators. It discusses how reactive streams like Flux and Mono work in Project Reactor and how Spring WebFlux allows building reactive web applications that can handle high concurrency with low latency. Examples are provided of building reactive data repositories, handling streaming responses with backpressure, and orchestrating remote service calls reactively.
This document provides an overview of reactive applications in Java using Project Reactor. It discusses the challenges of modern applications and how reactive programming addresses these challenges through asynchronous, non-blocking architectures. It introduces key concepts of reactive programming like Flux, Mono, operators, and backpressure. It also covers Project Reactor specifics like threading model, debugging, testing and learning resources. The goal is to explain why reactive programming is useful and provide an introduction to building reactive applications in Java with Project Reactor.
Today almost every product has an API, to integrate in other products or to made the data available to the outside world. Most API’s are using traditional patterns and technology. With the rise of Angular, React and other modern frameworks there is a need for non blocking API’s. Meet Reactive streams, like Spring Webflux, to super charge your API.
In this session I will tell about and show you Reactive API’s and more
Reactive solutions using java 9 and spring reactorOrenEzer1
This document discusses reactive programming concepts using Java 9 and Spring Reactor. It introduces reactive streams interfaces in Java 9 like Publisher, Subscriber, and Subscription. It then covers Spring Reactor implementations of these interfaces using Mono and Flux. Code examples are provided for creating simple reactive streams and combining them using operators. The threading model and use of schedulers in Spring Reactor is also briefly explained.
Building RESTFUL APIs with Spring WebfluxKnoldus Inc.
Have you ever struggled with the saturation of thread pools when you’re dealing with thousands of requests at a time? This problem of synchronous request processing is common with traditional MVC applications.
This is where Spring WebFlux enters the picture. It empowers you to build applications with a reactive programming paradigm in an asynchronous, non-blocking, and event-driven manner.
This webinar will deal with this concept and help you leverage the principles of reactive programming to develop microservices with the Spring WebFlux framework.
The agenda of the webinar will be as follows -
~ Introduction to reactive programming with Java
~ Build a microservice with Spring Webflux and writing unit test
cases for it.
~ Using WebClient to leverage external services
Spring WebFlux is a reactive web framework that uses Reactive Streams and non-blocking behavior to provide better scalability than traditional Spring MVC. It uses a small number of threads to handle requests asynchronously through reactive programming. Spring WebFlux supports both annotation-based and functional programming models for building reactive server-side web applications that can handle HTTP requests and WebSockets in a non-blocking manner through reactive streams. Router functions route incoming requests to handler functions based on matching predicates.
The document provides an overview of reactive programming and Spring WebFlux. It defines reactive programming as an asynchronous paradigm concerned with data streams and change propagation. It discusses why reactive programming is useful for handling back-pressure, communicating change, and improving scalability and performance. It also summarizes key concepts in reactive programming like Project Reactor's Mono and Flux types, and how Spring WebFlux allows developing reactive applications with annotated controllers or functional routing.
Reactive Card Magic: Understanding Spring WebFlux and Project ReactorVMware Tanzu
Spring Framework 5.0 and Spring Boot 2.0 contain groundbreaking technologies known as reactive streams, which enable applications to utilize computing resources efficiently.
In this session, James Weaver will discuss the reactive capabilities of Spring, including WebFlux, WebClient, Project Reactor, and functional reactive programming. The session will be centered around a fun demonstration application that illustrates reactive operations in the context of manipulating playing cards.
Presenter : James Weaver, Pivotal
Reactive programming is a new concept that is catching everyone’s eyes these days. The concept has been adopted by the various aspects of software engineering be it application development or DevOps. Our software development languages are also not untouched from it.
So, how can JAVA which has such a large community refrain itself from going reactive? The foundational topics for this talk will revolve around the ideas of reactive programming and what steps JAVA has taken towards being reactive. This would involve the latest buzz words in the market: Reactive streams, Reactive stream specification, the concept of mono and flux. We will also be touching how spring has used these features of reactive streams to make a new API development framework: Spring Boot Webflux. We hope the talk will help to understand Reactive programming aspects of JAVA and it will not bewilder the users as now they know that it’s a coding style that centres on the effective management of changes with async data streams.
1) Reactive programming is a new programming paradigm that is asynchronous and non-blocking, treating data flows as event-driven streams.
2) Traditional REST APIs are synchronous and blocking with limitations on concurrent users, while reactive programming supports asynchronous operations, uses fewer threads, and enables back pressure on data streams.
3) Key aspects of reactive programming include reactive streams specifications, publishers that represent data sources, subscribers, and asynchronous non-blocking libraries like RxJava and Project Reactor that implement the specifications.
Ready for a deep dive into the world's most challenging programming paradigm? Reactive programming can simplify asynchronous and event-driven applications, but without a strong understanding, it can lead to frustration, recurring patchwork, missed deadlines, and costly bugs.
In this intensive three-hour session, we'll transition a traditional Spring application to WebFlux, revealing patterns and aanti-patterns when working with repositories, REST APIs, queues, and legacy libraries. You'll gain a clear understanding of often overlooked but critical aspects like subscribe signal, errors, cancellation, and signal loss. As a bonus, we'll debate the future of Reactive vs Virtual Threads, production-ready in Java 21.
This session is crucial for developers already working with reactive programming or those intending to make the leap.
This document provides an overview of reactive programming and the Reactor library. It defines key concepts like:
- Reactive programming is concerned with propagating change via asynchronous data streams.
- The Reactor library implements the Reactive Streams specification and provides abstractions like Flux and Mono to easily create and compose reactive streams.
- Operators like map(), flatMap(), and publishOn() allow transforming and executing streams on different threads.
- Reactor supports both blocking and non-blocking pipelines that can run synchronously or asynchronously through operators and concurrency models like publishOn().
In recent times, Reactive Programming has gained a lot of popularity. It is not a “silver bullet” nor it is a solution for every problem. Yet, it is a paradigm to build applications which are non-blocking, event-driven and asynchronous and require a small number of threads to scale. Spring Framework 5 embraces Reactive Streams and Reactor for its own reactive use, as well as in many of its core APIs. It also adds an ability to code in a declarative way, as opposed to imperatively, resulting in more responsive and resilient applications. On top of that, you are given an amazing toolbox of functions to combine, create and filter any data stream. It becomes easy to support input and output streaming scenarios for microservices, scatter/gather, data ingestion, and so on. This presentation is about support and building blocks for reactive programming, that come with the latest versions of Spring Framework 5 and Spring Boot 2.
Spring Framework 5.0による Reactive Web Application #JavaDayTokyoToshiaki Maki
The document discusses reactive programming and the Spring Framework 5.0 release. It provides an overview of reactive programming concepts like asynchronous non-blocking applications. It also discusses Reactive Streams and libraries like Reactor. Finally, it covers new features in Spring Framework 5.0 like performance improvements, support for JDK 9, and the introduction of reactive APIs in Spring.
Reactive Programming In Java Using: Project ReactorKnoldus Inc.
The session provides details about reactive programming with reactive streams. The purpose of Reactive Streams is to provide a standard for asynchronous stream processing with non-blocking backpressure.”
This concept is explained using Project reactor.
This document provides an introduction to reactive programming and Spring Web Flux. It defines reactive programming as managing asynchronous and non-blocking data flows. Spring Web Flux allows building reactive web applications using either annotations or functional programming. It uses project Reactor's Mono and Flux types to implement the reactive streams specification. Spring supports integrating different servers like Netty, Undertow, Tomcat and Jetty using bridges to reactive streams.
En esta presentación para el IBM Java Talks, hablé sobre Spring Webflux y cómo hace uso de Project Reactor y Rx Java para integrar un módulo de programación reactiva dentro de su set.
Mostré un pequeño demo de una aplicación rest que se puede consultar en la siguiente URL:
https://github.com/gdljug/REACTIVE-SPRING-BOOT-API
SpringOne Platform 2017
Stéphane Maldini, Pivotal; Simon Basle, Pivotal
"In 2016, Project Reactor was the foundation before Spring Reactive story, in particular with Reactor Core 3.0 fueling our initial Spring Framework 5 development.
2017 and 2018 are the years Project Reactor empowers the final Spring Framework 5 GA and an entire ecosystem, thus including further refinement, feedbacks and incredible new features. In fact, the new Reactor Core 3.1 and Reactor Netty 0.7 are the very major versions used by the like of Spring Boot 2.0, and they have dramatically consolidated around a simple but yet coherent API.
Discover those changes and the new Reactor capabilities including support for Reactive AOP, Observability, Tracing, Error Strategies for long-running streams, new Netty driver, improved test support, community driven initiatives and much more
Finally, the first java framework & ecosystem gets the reactive library it needs !"
The document discusses reactive programming with Spring, including why reactive systems are needed, key concepts of reactive programming, and Spring's reactive frameworks. It notes that reactive systems aim to be responsive, resilient, and elastic. Spring supports reactive programming through projects like WebFlux, which uses reactive types like Mono and Flux. The document provides an overview of reactive concepts and demonstrates a simple reactive REST application using Spring WebFlux.
Reactive programming with Pivotal's reactorVMware Tanzu
VICTOR GRAZI VP, NOMURA
Reactive Programming is an emerging paradigm for non-blocking concurrent programming. This means you can have multiple workers without allocating resources to multiple threads! In this presentation we will take a look at what reactive programming is and why it has become so popular. Then we will look at Pivotal's Reactor implementation, along with a deep dive into some coding examples.
Full Stack Reactive with React and Spring WebFlux Workshop - KCDC 2019Matt Raible
You have streaming data and want to expose it as reactive streams with Spring Boot. Great! Spring WebFlux makes that pretty easy. But what about the UI? Can you stream that data to the UI and have it be reactive and constantly updating too? This workshop explores techniques for making your app fully reactive with Spring WebFlux and React.
Instructions: https://github.com/oktadeveloper/okta-spring-webflux-react-example/blob/react-app/workshop.adoc
Full Stack Reactive Java - SpringOne Tour DallasVMware Tanzu
This document provides an overview of reactive programming with Spring Framework 5, Spring Boot 2, and Project Reactor. It introduces the speaker as an author, speaker, architect and developer who seeks a better way. It then defines reactive programming as non-blocking, event-driven applications that scale with few threads using backpressure. The document also lists the 4 interfaces of Reactive Streams and notes that Project Reactor will provide a quick overview of it. It concludes by thanking the audience and providing contact details for the speaker.
”Everything is a stream“ - This often cited mantra indicates why Reactive Programming is such a powerful tool for handling data flows in almost every part of an application. Reactive Programming has experienced a significant growth in popularity in recent years. But its growing popularity also leads to a Babylonian confusion: the term ”Reactive“ has become overloaded. To understand what Reactive Programming is, this talk surveys the landscape sharpened by trends like Reactive Streams, Reactive Extensions, and Reactive Systems. It then summarizes the basic principles of Reactive Programming by looking at the Reactor library. Finally, it discusses an application of Reactive Programming that lies beyond the standard tutorial examples: an implementation of the BigPipe pattern using Spring 5.
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Building RESTFUL APIs with Spring WebfluxKnoldus Inc.
Have you ever struggled with the saturation of thread pools when you’re dealing with thousands of requests at a time? This problem of synchronous request processing is common with traditional MVC applications.
This is where Spring WebFlux enters the picture. It empowers you to build applications with a reactive programming paradigm in an asynchronous, non-blocking, and event-driven manner.
This webinar will deal with this concept and help you leverage the principles of reactive programming to develop microservices with the Spring WebFlux framework.
The agenda of the webinar will be as follows -
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~ Build a microservice with Spring Webflux and writing unit test
cases for it.
~ Using WebClient to leverage external services
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The document provides an overview of reactive programming and Spring WebFlux. It defines reactive programming as an asynchronous paradigm concerned with data streams and change propagation. It discusses why reactive programming is useful for handling back-pressure, communicating change, and improving scalability and performance. It also summarizes key concepts in reactive programming like Project Reactor's Mono and Flux types, and how Spring WebFlux allows developing reactive applications with annotated controllers or functional routing.
Reactive Card Magic: Understanding Spring WebFlux and Project ReactorVMware Tanzu
Spring Framework 5.0 and Spring Boot 2.0 contain groundbreaking technologies known as reactive streams, which enable applications to utilize computing resources efficiently.
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Presenter : James Weaver, Pivotal
Reactive programming is a new concept that is catching everyone’s eyes these days. The concept has been adopted by the various aspects of software engineering be it application development or DevOps. Our software development languages are also not untouched from it.
So, how can JAVA which has such a large community refrain itself from going reactive? The foundational topics for this talk will revolve around the ideas of reactive programming and what steps JAVA has taken towards being reactive. This would involve the latest buzz words in the market: Reactive streams, Reactive stream specification, the concept of mono and flux. We will also be touching how spring has used these features of reactive streams to make a new API development framework: Spring Boot Webflux. We hope the talk will help to understand Reactive programming aspects of JAVA and it will not bewilder the users as now they know that it’s a coding style that centres on the effective management of changes with async data streams.
1) Reactive programming is a new programming paradigm that is asynchronous and non-blocking, treating data flows as event-driven streams.
2) Traditional REST APIs are synchronous and blocking with limitations on concurrent users, while reactive programming supports asynchronous operations, uses fewer threads, and enables back pressure on data streams.
3) Key aspects of reactive programming include reactive streams specifications, publishers that represent data sources, subscribers, and asynchronous non-blocking libraries like RxJava and Project Reactor that implement the specifications.
Ready for a deep dive into the world's most challenging programming paradigm? Reactive programming can simplify asynchronous and event-driven applications, but without a strong understanding, it can lead to frustration, recurring patchwork, missed deadlines, and costly bugs.
In this intensive three-hour session, we'll transition a traditional Spring application to WebFlux, revealing patterns and aanti-patterns when working with repositories, REST APIs, queues, and legacy libraries. You'll gain a clear understanding of often overlooked but critical aspects like subscribe signal, errors, cancellation, and signal loss. As a bonus, we'll debate the future of Reactive vs Virtual Threads, production-ready in Java 21.
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This document provides an overview of reactive programming and the Reactor library. It defines key concepts like:
- Reactive programming is concerned with propagating change via asynchronous data streams.
- The Reactor library implements the Reactive Streams specification and provides abstractions like Flux and Mono to easily create and compose reactive streams.
- Operators like map(), flatMap(), and publishOn() allow transforming and executing streams on different threads.
- Reactor supports both blocking and non-blocking pipelines that can run synchronously or asynchronously through operators and concurrency models like publishOn().
In recent times, Reactive Programming has gained a lot of popularity. It is not a “silver bullet” nor it is a solution for every problem. Yet, it is a paradigm to build applications which are non-blocking, event-driven and asynchronous and require a small number of threads to scale. Spring Framework 5 embraces Reactive Streams and Reactor for its own reactive use, as well as in many of its core APIs. It also adds an ability to code in a declarative way, as opposed to imperatively, resulting in more responsive and resilient applications. On top of that, you are given an amazing toolbox of functions to combine, create and filter any data stream. It becomes easy to support input and output streaming scenarios for microservices, scatter/gather, data ingestion, and so on. This presentation is about support and building blocks for reactive programming, that come with the latest versions of Spring Framework 5 and Spring Boot 2.
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The session provides details about reactive programming with reactive streams. The purpose of Reactive Streams is to provide a standard for asynchronous stream processing with non-blocking backpressure.”
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This document provides an introduction to reactive programming and Spring Web Flux. It defines reactive programming as managing asynchronous and non-blocking data flows. Spring Web Flux allows building reactive web applications using either annotations or functional programming. It uses project Reactor's Mono and Flux types to implement the reactive streams specification. Spring supports integrating different servers like Netty, Undertow, Tomcat and Jetty using bridges to reactive streams.
En esta presentación para el IBM Java Talks, hablé sobre Spring Webflux y cómo hace uso de Project Reactor y Rx Java para integrar un módulo de programación reactiva dentro de su set.
Mostré un pequeño demo de una aplicación rest que se puede consultar en la siguiente URL:
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Whether you’re building internal tools, public portals, or powering automation – this webinar is your starting point to real-time data delivery.
Exploring the advantages of on-premises Dell PowerEdge servers with AMD EPYC processors vs. the cloud for small to medium businesses’ AI workloads
AI initiatives can bring tremendous value to your business, but you need to support your new AI workloads effectively. That means choosing the best possible infrastructure for your needs—and many companies are finding that the cloud isn’t right for them. According to a recent Rackspace survey of IT executives, 69 percent of companies have moved some of their applications on-premises from the cloud, with half of those citing security and compliance as the reason and 44 percent citing cost.
On-premises solutions provide a number of advantages. With full control over your security infrastructure, you can be certain that all compliance requirements remain firmly in the hands of your IT team. Opting for on-premises also gives you the ability to design your infrastructure to the precise needs of that team and your new AI workloads. Depending on the workload, you may also see performance benefits, along with more predictable costs. As you start to build your next AI initiative, consider an on-premises solution utilizing AMD EPYC processor-powered Dell PowerEdge servers.
AI Agents in Logistics and Supply Chain Applications Benefits and ImplementationChristine Shepherd
AI agents are reshaping logistics and supply chain operations by enabling automation, predictive insights, and real-time decision-making across key functions such as demand forecasting, inventory management, procurement, transportation, and warehouse operations. Powered by technologies like machine learning, NLP, computer vision, and robotic process automation, these agents deliver significant benefits including cost reduction, improved efficiency, greater visibility, and enhanced adaptability to market changes. While practical use cases show measurable gains in areas like dynamic routing and real-time inventory tracking, successful implementation requires careful integration with existing systems, quality data, and strategic scaling. Despite challenges such as data integration and change management, AI agents offer a strong competitive edge, with widespread industry adoption expected by 2025.
Top 25 AI Coding Agents for Vibe Coders to Use in 2025.pdfSOFTTECHHUB
I've tested over 50 AI coding tools in the past year, and I'm about to share the 25 that actually work. Not the ones with flashy marketing or VC backing – the ones that will make you code faster, smarter, and with way less frustration.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2025/06/state-space-models-vs-transformers-for-ultra-low-power-edge-ai-a-presentation-from-brainchip/
Tony Lewis, Chief Technology Officer at BrainChip, presents the “State-space Models vs. Transformers for Ultra-low-power Edge AI” tutorial at the May 2025 Embedded Vision Summit.
At the embedded edge, choices of language model architectures have profound implications on the ability to meet demanding performance, latency and energy efficiency requirements. In this presentation, Lewis contrasts state-space models (SSMs) with transformers for use in this constrained regime. While transformers rely on a read-write key-value cache, SSMs can be constructed as read-only architectures, enabling the use of novel memory types and reducing power consumption. Furthermore, SSMs require significantly fewer multiply-accumulate units—drastically reducing compute energy and chip area.
New techniques enable distillation-based migration from transformer models such as Llama to SSMs without major performance loss. In latency-sensitive applications, techniques such as precomputing input sequences allow SSMs to achieve sub-100 ms time-to-first-token, enabling real-time interactivity. Lewis presents a detailed side-by-side comparison of these architectures, outlining their trade-offs and opportunities at the extreme edge.
Guide to Spring Reactive Programming using WebFlux
1. Guide to Spring Reactive Programming using
WebFlux
Reactive programming is a programming paradigm that promotes an asynchronous,
non-blocking, event driven approach to data processing. Reactive programming
involves modelling data and events as observable data streams and implementing
data processing routines to react to the changes in those streams.
In the reactive style of programming, we make a request for the resource and start
performing other things. When the data is available, we get the notification along
with the data in the form of call back function. In the callback function, we handle
the response as per application /user needs.
Features of Reactive Programming
• Asynchronous & Non-blocking
• Functional style of coding
2. • Data flow as event driven stream
• Backpressure on data streams
When considering whether to use Spring MVC or Spring WebFlux, there are various
factors you must consider.
Spring MVC: It’s based on a servlet API and follows an imperative programming
model. This means you write code in a step-by-step manner, which is generally easier
to follow.
Spring WebFlux: It offers a reactive programming model. Reactive programming is
about handling asynchronous streams of data. This requires a change in thinking and
can be more challenging than the traditional imperative model.
Spring MVC: If you are familiar with traditional web application development, Spring
MVC’s imperative model might seem more straightforward. It’s easier to read, write,
and understand for developers accustomed to this approach.
Spring WebFlux: Writing reactive code can initially seem complex because of the
shift in mindset. However, for some use cases, like streaming data, it can simplify
your code.
Spring MVC: Debugging is typically more straightforward with an imperative model
because the call stacks are more predictable and easier to trace.
3. Spring WebFlux: Debugging reactive streams can be tricky, especially for developers
new to the reactive paradigm. However, tools and practices are evolving to better
support this.
Spring MVC: Works naturally with blocking resources like traditional RDBMS using
JDBC or JPA (Java Persistence API).
Spring WebFlux: If you have blocking dependencies like traditional databases, you
might not get the full benefits of the reactive model. However, reactive databases
like MongoDB Reactive, Cassandra Reactive, etc., can be integrated natively with
WebFlux.
Spring MVC: Uses a thread-per-request model. For a high number of simultaneous
connections, this can lead to a large number of threads, which may not be efficient.
Spring WebFlux: Uses an event-loop concurrency model, which can handle a vast
number of simultaneous connections with a smaller number of threads. It’s designed
for high concurrency.
Spring MVC: Typically runs on servlet containers like Tomcat, Jetty, etc.
Spring WebFlux: Runs on reactive runtimes like Netty. This provides non-blocking
and highly scalable operations, suitable for high-performance systems.
Spring MVC: Typically uses annotated controllers.
Spring WebFlux: In addition to annotated controllers, WebFlux supports functional
endpoints which allow for programmatic route definitions.
Spring WebFlux:
As we know, Spring provides Web MVC framework to handle the HTTP requests, but
it is Blocking & Non-Reactive in nature, so to support reactive programming Spring
provides one more web framework in Spring 5 (includes in Spring Boot 2.0) called
WebFlux.
4. It is a reactive-stack web framework that is fully non-blocking, supports reactive
streams back pressure. It uses project Reactor as a reactive library. The Reactor is a
Reactive Streams Library and therefore, all of its operators support non-blocking
back pressure.
It uses two publishers:
• Mono
• Flux
MONO:
A mono is a specialized Publisher that emits at most one item and then optionally
terminates with an onComplete signal or an onError signal. In short, it returns 0 or 1
element.
• Mono is another implementation of Publisher.
• It emits at most one item and then (optionally) terminates with an
onComplete signal or an onError signal.
• Like Flux, Mono is also asynchronous in nature.
Mono noData = Mono.empty();
Mono data = Mono.just(“rishi”);
FLUX:
A flux is a standard Publisher representing an asynchronous sequence of 0 to N
emitted items, optionally terminated by either a completion signal or an error. These
three types of signals translate to calls to a downstream subscriber’s onNext,
onComplete, or onError methods.
• Flux is an implementation of Publisher.
• It will emit 0 to N elements and/or a complete or an error call.
• Stream pipeline is synchronous whereas Flux pipeline is completely
asynchronous. It will emit values only when there is a downstream subscriber.
To subscribe, we need to call the subscribe method on Flux. There are different
variants of the subscribe method available, which we need to use as per the need:
Flux flux1 = Flux.just(“foo”, “bar”, “foobar”);
5. Flux flux2 = Flux.fromIterable(Arrays.asList(“A”, “B”, “C”));
Flux flux3 = Flux.range(5, 3);
// subscribe
flux.subscribe();
Frequently used operations on Mono/Flux
• just(-): Create a new Mono that emits the specified item, which is captured at
instantiation time.
• fromArray(-): Create a Flux that emits the items contained in the provided
array.
• fromIterable(-): Create a Flux that emits the items contained in the provided
iterable. The Iterable.iterator() method will be invoked at least once and at
most twice for each subscriber.
• fromStream(-): Create a Flux that emits the items contained in a Stream
created by the provided Supplier for each subscription. The Stream is closed
automatically by the operator on cancellation, error, or completion.
• empty(): Create a Flux that completes without emitting any item.
• doOnNext(-): Add behaviour (side-effect) triggered when the Flux emits an
item.
• doOnComplete(-): Add behaviour (side-effect) triggered when the Flux
completes successfully.
• doOnError(-): Add behaviour (side-effect) triggered when the Flux completes
with an error.
• map(-): Transform the items emitted by this Flux by applying a synchronous
function to each item.
• flatMap(-): Transform the item emitted by this Mono asynchronously,
returning the value emitted by another Mono (possibly changing the value
type).
• subscribe(-, -, -): Subscribe a Consumer to this Flux that will consume all the
elements in the sequence. It will request an unbounded demand.
• log(): Observe all Reactive Streams signals and trace them using Logger
support. Default will use Level.INFO and java.util.logging. If SLF4J is available,
it will be used instead.
6. • delayElements(-): Delay each of this Flux elements (Subscriber.onNext signals)
by a given Duration. Signals are delayed and continue the parallel default
Scheduler, but empty sequences or immediate error signals are not delayed.
• block(): Subscribe to this Mono and block indefinitely until a next signal is
received. Returns that value, or null if the Mono completes empty. In case the
Mono errors, the original exception is thrown (wrapped in a RuntimeException
if it was a checked exception)
Working with Spring Web Flux –
Understanding the Reactive nature
Requirement: Send Promos to all the customers of an e-Commerce website
Step-1: Create a Spring Boot project using Maven (Choose Spring Boot version 2.0 or
later)
Step-2: Add the below spring-boot-starter-webflux dependency in pom.xml
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-webflux</artifactId>
</dependency>
This dependency includes the below dependencies
• spring-webflux framework
• reactor-core that we need for reactive streams
reactor-netty (the default server that supports reactive streams). Any other servlet
3.1+ containers like Tomcat, Jetty or non-servlet containers like Undertow can be
used as well
Version will be picked from spring-boot-starter-parent dependency version
Step-3: Create a Customer DTO class with the fields Id, Name & Email Id
7. Step-4: Create a Customer Repo with 2 functions loadCustomers(),
loadCustomerStream() as in the below snapshot.
8. Step-5: Create a Customer Service with 2 functions, one is to send promos to list of
customers, another is to send promos to customer stream
9. Step-6: Create a Customer REST Controller with 2 end points as in the below
screenshot
Summary:
Spring introduced a Multi-Event Loop model to enable a reactive stack known as
WebFlux. It is a fully non-blocking and annotation-based web framework built on
Project Reactor which allows building reactive web applications on the HTTP layer. It
provides support for popular inbuilt severs like Netty, Undertow, and Servlet 3.1
containers.
WebFlux is also relevant for applications that need scalability or to stream request
data in real time. While implementing a micro-service in WebFlux we must consider
that the entire flow uses reactive and asynchronous programming and none of the
operations are blocking in nature.
Originally published by: Guide to Spring Reactive Programming using WebFlux