compose() vs. transform() vs. as() vs. map() in Flux and Mono

Question

Recently, I decided to try spring 5 with projectreactor.io (io.projectreactor:3.1.1).

Does anyone know what the best case of using this functions? What cons and pros of using each of them and where they should be used?

Good examples will be helpful.

Answer 1

You have two broadly different categories of operators here:

Operators that work on the Flux itself

transform and transformDeferred are for code mutualization

When you compose chains of operators regularly and you have common operator usage patterns in your application, you can mutualize this code or give it a more descriptive name by using transform and transformDeferred.

The difference between the two is when the mutualized operators are applied: transform applies them at instantiation, while transformDeferred applies them at subscription (allowing for dynamic choice of the added operators).

Have a look at the reference documentation for more details and examples.

note: transformDeferred was called compose in versions prior to 3.3.0

as

This is a convenience shortcut to apply a Function to the whole Flux while keeping the whole code in a fluent style.

The major differentiator with transform* operators is that this one doesn't enforce a particular return type. It is all driven by the Function you use, and could for instance be used for testing with a StepVerifier in a fluent style:

Flux.just("test")
    .map(String::length)
    .as(StepVerifier::create)
    //from there on we're dealing with the StepVerifier API
    .expectNext(4)
    .verifyComplete();

The example shown in the javadoc uses this approach to convert to a Mono using Mono::from, which is a bit confusing because the return type is quite close to Flux.

Note that this approach can also helps with external operators that are implemented in a factory method style to "extend" the Flux API

Take reactor-addons MathFlux for example, and compare:

MathFlux.sumInt(Flux.range(1, 10)
                    .map(i -> i + 2)
                    .map(i -> i * 10))
        .map(isum -> "sum=" + isum);

To:

Flux.range(1, 10)
    .map(i -> i + 2)
    .map(i -> i * 10)
    .as(MathFlux::sumInt)
    .map(isum -> "sum=" + isum)

(this can help you deal with the fact that, unlike Kotlin, Java doesn't have extension methods :) )

Operator that works on the data that goes through the Flux

map is all about the data. It applies a 1-1 transformation function to each element in the source, as they become available.

In the MathFlux example above, map is successively used to add 2 to each original integer, then again to multiply each number in the sequence by 10, then a third time at the end to produce a String out of each sum.