Reactive Programming with Reactor 3

Reactor
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Transform

Description

Reactor ships with several operators that can be used to transform data.

Practice

In the first place, we will capitalize a String. Since this is a simple 1-1 transformation with no expected latency, we can use the map operator with a lambda transforming a T into a U.

Capitalize data on Mono

We can use exactly the same code on a Flux, applying the mapping to each element as it becomes available.

Capitalize data on Flux

Now imagine that we have to call a webservice to capitalize our String. This new call can have latency so we cannot use the synchronous map anymore. Instead, we want to represent the asynchronous call as a Flux or Mono, and use a different operator: flatMap.

flatMap takes a transformation Function that returns a Publisher<U> instead of a U. This publisher represents the asynchronous transformation to apply to each element. If we were using it with map, we'd obtain a stream of Flux<Publisher<U>>. Not very useful.

But flatMap on the other hand knows how to deal with these inner publishers: it will subscribe to them then merge all of them into a single global output, a much more useful Flux<U>. Note that if values from inner publishers arrive at different times, they can interleave in the resulting Flux.

Async transformation
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package io.pivotal.literx;
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