How does backpressure affect you in RxJava 2.0? How can you deal with it?
- [Manuel] Hi. Welcome to the second video,…Back Pressure in RxJava 2.0.…In the previous video, we learned a bit more about RxJava 2.…Now, it's time to talk about some features built in.…The video is going to be about back pressure…and how to handle it properly in RxJava 2.…In the first volume, we said…that back pressure happens when the source of information…overflows the consumer with data.…Dealing with back pressure provides resilience,…since it ensures that the elements involved…participate in flow control.…As we said, pulls works well when consumers…are faster than the source of information,…but it's fairly difficult to predict…from one moment to the next one…whether the source will be faster than a consumer…over a period of time.…
RxJava 1 didn't have back pressure built in,…but Reactive Streams defines the stream processing…with non-blocking back pressure,…so we can expect for RxJava 2…to offer mechanisms to deal with back pressure natively.…Imagine we are getting some touch events…that are coming in as fast…
AuthorManuel Vicente Vivo
This course was created and produced by Packt Publishing. We are honored to host this training in our library.
- What is reactive programming?
- Java 9 reactive features
- Creating and observing sources with RxJava
- Unit testing
- Akka streams in a reactive environment
- Building a sample reactive application
Skill Level Intermediate
1. What Is Reactive Programming?
2. Reactivity in Java 9
3. Introducing RxJava 2.0
5. Concurrency and Unit Testing
6. Akka Streams
7. Real-Life Reactive Application
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