One of the main mechanisms behind Reactive Programming is backpressure. In this article we’ll take a look at the concept, and some of the advantages it creates when working with Reactive Streams. The concept of backpressure in Reactive Streams is as elegant as it is powerful. It will enable the use of slow Consumers within … Continue reading "Backpressure in Project Reactor: Saving your Subscribers from drowning"
Read MoreAuthor: Kristof Van Sever
Flux Caching in Project Reactor: Replaying past data
In the article Flux Sharing in Project Reactor: From one to many we looked at how we can attach multiple Fluxes to an initial Flux by sharing it, to create multiple substreams from our original Reactive stream. This offers quite a bit of extra power. We can “feed” data to different subsystems that can consume … Continue reading "Flux Caching in Project Reactor: Replaying past data"
Read MoreFlux Sharing in Project Reactor: From one to many
Reactive Applications often require Reactive Streams to be subscribed to by multiple Subscribers at the same time. For example when the same information streams needs to be used by different components in the application, or when we want to let the data stream to different users. Especially in real-time applications this can be a huge … Continue reading "Flux Sharing in Project Reactor: From one to many"
Read MoreReactive Spring Data MongoDB: Tailable Cursors
In our previous article on the new Reactive Spring Data, we took a basic look at what MongoDB had to offer through its Reactive driver. We were able to send and receive information from and to our database in an event-stream-driven way. Instead of having to wait for the full result of our database call, … Continue reading "Reactive Spring Data MongoDB: Tailable Cursors"
Read MoreReactive Spring Data Introduction
When building applications, we often want to save information in a database. Databases are notoriously I/O-bound, meaning that when a CPU has to wait for its results the application’s threads get blocked, and it is wasting a lot of valuable cycles. These cycles are far better off being used to do other useful work, like … Continue reading "Reactive Spring Data Introduction"
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