Reactive Programming

Why?

• Compare to concurrency APIs (Future and CompletatbleFuture)
  • Much simpler than the manual concurrent way
  • Few reusable flexible functions
  • Combine and reuse in powerful ways

Stream

• Represent a sequence of data

• Focus on computations

• vs collections which focus on storage

• Internal iteration

• Operators

  • map
  • filter
  • flatMap
  • findFirst
  • ... and many more

Design Patterns

• Iterator
• Observer

Reactive Streams

• subscribe - the glue that connects an observer to an Observable
• publisher and subscriber

• Flux - async sequence of events, return 0 or n times
• Mono - async item, return 0 or 1 time

What's coming?

• An item

• A complete event, a terminate event

• A failure event, a terminate event

• Operators

  • filter
  • map
  • defaultIfEmpty
  • log

        List<Integer> numbers = ReactiveSources
        .intNumbersFlux()
        .log()
        .toStream()
        .collect(Collectors.toList());

    [ INFO] (main) onSubscribe(FluxConcatMap.ConcatMapImmediate)
    [ INFO] (main) request(256)
    [ INFO] (parallel-1) onNext(1)
    [ INFO] (parallel-2) onNext(2)
    [ INFO] (parallel-3) onNext(3)
    [ INFO] (parallel-4) onNext(4)
    [ INFO] (parallel-5) onNext(5)
    [ INFO] (parallel-6) onNext(6)
    [ INFO] (parallel-7) onNext(7)
    [ INFO] (parallel-8) onNext(8)
    [ INFO] (parallel-9) onNext(9)
    [ INFO] (parallel-10) onNext(10)
    [ INFO] (parallel-10) onComplete()
    

  • subscribe

Return values

Error

• Terminal event
• Original sequence does not continue
• Calls the onError method of the Subscriber