20 Spring WebFlux Interview Questions and Answers
Prepare for the types of questions you are likely to be asked when interviewing for a position where Spring WebFlux will be used.
Prepare for the types of questions you are likely to be asked when interviewing for a position where Spring WebFlux will be used.
Spring WebFlux is a popular Java-based web development framework. If you’re applying for a position that involves Java development, it’s likely that the interviewer will ask you questions about your experience with Spring WebFlux. Knowing how to properly answer these questions can help you make a strong impression and improve your chances of getting the job. In this article, we discuss the most commonly asked Spring WebFlux questions and provide tips on how to answer them.
Here are 20 commonly asked Spring WebFlux interview questions and answers to prepare you for your interview:
WebFlux is a reactive programming model for building web applications. It is built on top of the Reactive Streams API and provides a way to build event-driven, non-blocking applications.
Spring Webflux is a non-blocking, reactive framework for building web applications. This means that instead of the traditional request/response model, Webflux uses an event-driven model where the application reacts to events as they occur. This can lead to better performance and scalability, as well as a more responsive user experience. Spring MVC is the traditional, blocking framework for building web applications.
You can create a web service using Spring Boot Webflux by following these steps:
1. Create a Spring Boot project
2. Add the WebFlux dependency
3. Create a controller class and annotate it with @RestController
4. Create a request mapping method and annotate it with @GetMapping
5. Run the application
The main components of Spring Webflux are the RouterFunction and the HandlerFunction. The RouterFunction is responsible for mapping incoming requests to the appropriate HandlerFunction. The HandlerFunction is responsible for handling the request and returning a response.
Yes, it is possible to use reactive programming in Spring Webflux. This can be accomplished by using the reactive programming support that is built into the Spring Framework. This support allows for the creation of reactive components that can be used in conjunction with Spring Webflux to create reactive applications.
Reactive programming can provide benefits over traditional techniques in situations where you need to process a large number of small requests quickly, or where you need to be able to handle a variable number of requests. Additionally, reactive programming can make it easier to reason about your code, since you can think about it in terms of data flows instead of individual threads of execution.
Blocking calls are those where the thread making the call is blocked until the call returns. Non-blocking calls are those where the thread making the call is not blocked, and can continue to do other work while the call is being processed. I think that non-blocking calls are better because they allow for better utilization of resources.
Event looping is a process whereby a program continually checks for new events or tasks and then processes them as they come in. This is important for asynchronous processing because it allows the program to continue running even while waiting for new tasks to come in, which can improve efficiency and performance.
There is no definitive answer to this question, as it depends on the specific situation and what you are trying to achieve. However, in general, an async/await approach may be preferable if you are working with code that is already asynchronous or if you need to perform multiple asynchronous operations in a row. A promise approach may be more appropriate if you are working with code that is not asynchronous or if you only need to perform a single asynchronous operation.
The Future class is used to represent the result of an asynchronous computation. This is useful in a Spring WebFlux application, where you may need to perform a long-running task in the background and then return the result to the caller. By using a Future, you can start the computation immediately and then wait for it to finish before returning the result.
When you execute a task in parallel, you are essentially running multiple tasks at the same time. This can be useful when you want to speed up the execution of a task by running it on multiple processors or cores. It can also be useful for running tasks that are independent of each other, so that one task does not have to wait for the other to finish before it can start.
Real-world applications that can benefit from reactive programming include those that deal with high volumes of data or those that need to be able to handle a large number of concurrent users. Reactive programming can help to make these applications more responsive and scalable.
The best way to handle errors while performing asynchronous operations is to use the onErrorResume method. This will allow you to resume the operation in the event of an error, which can help to prevent the entire operation from being aborted.
Reactive programming can provide a significant performance boost over traditional programming techniques, but it comes at the cost of increased complexity. If you are willing to trade off some simplicity for the sake of performance, then reactive programming may be the right choice for your project.
Reactor is a library that helps you build reactive applications in Java. It is based on the Reactive Streams specification. The main components of Reactor are the Publisher and the Subscriber. The Publisher is responsible for emitting data, and the Subscriber is responsible for consuming that data.
The Flux API is a reactive programming library for Java that allows developers to easily build asynchronous applications. The library is based on the Reactive Streams specification, and provides a wide variety of operators that can be used to manipulate data streams.
A Publisher is a reactive component that emits a stream of data. The two main interfaces are Publisher and Subscriber.
A hot publisher is a publisher that emits data even if there is no Subscriber subscribed to it. A cold publisher is a publisher that only emits data when there is at least one Subscriber subscribed to it.
Backpressure operators are a type of operator specifically designed for use with reactive streams. They help to ensure that a stream does not become overwhelmed by too much data, and can instead process data at a rate that it can comfortably handle. This can help to avoid issues such as buffering and blocking, and can improve overall performance.
Throttling is a process of limiting the amount of data that can be transferred between two systems in a given period of time. This is often done to prevent one system from overloading another system with too much data, or to prevent one user from consuming too much of a shared resource.