Hands-On Reactive Programming in Spring 5

Composing and transforming Reactive Streams

When we build complicated reactive workflows, it is often necessary to use the same sequence of operators in a couple of different places. With the transform operator, we can extract such common pieces into separate objects and reuse them whenever required. Previously, we've transformed events within a stream. With the transform operator, we can augment the stream structure itself. Let's assume the following example:

Function<Flux<String>, Flux<String>> logUserInfo =                 // (1)    stream -> stream                                               //        .index()                                                   // (1.1)        .doOnNext(tp ->                                            // (1.2)            log.info("[{}] User: {}", tp.getT1(), tp.getT2()))     //        .map(Tuple2::getT2);                                       // (1.3)Flux.range(1000, 3)                                                // (2)    .map(i -> "user-" + i)                                         // .transform(logUserInfo) // ...