Why this flux isn’t executed in multiple threads?

I have the following example:

Flux.just(1,2,3,4,5,6,7,8)
    .flatMap(integer -> {
                 System.out.println("val:" + integer + ", thread:" + Thread.currentThread().getId()); 
                 return Mono.just(integer);
             }, 5)
    .repeat()
    .subscribeOn(Schedulers.parallel())
    .subscribe();

logs are as follows:

val:4, thread:14
val:5, thread:14
val:6, thread:14
val:7, thread:14
val:8, thread:14
val:1, thread:14
val:2, thread:14
val:3, thread:14

why the same thread everywhere?? How can i modify the example so it is executed in multiple threads?

Answer

If you want each repeated flux to be on a different thread, you can move the publishOn before, like this:

Flux.just(1,2,3,4,5,6,7,8)
        .publishOn(Schedulers.parallel()) // <- before
        .flatMap(integer -> {
           System.out.println("val:" + integer + ", thread:" + Thread.currentThread().getId()); 
           return Mono.just(integer);
        }, 5)
        .repeat()
        .subscribe();

The output is like that now:

val:1, thread:20
val:2, thread:20
val:3, thread:20
val:4, thread:20
val:5, thread:20
val:6, thread:20
val:7, thread:20
val:8, thread:20
val:1, thread:13
val:2, thread:13
val:3, thread:13
val:4, thread:13
val:5, thread:13
val:6, thread:13
val:7, thread:13
val:8, thread:13

If you want each integer to be in a different thread, you can do something like this:

Flux.just(1,2,3,4,5,6,7,8)
        .publishOn(Schedulers.parallel()) // <- Each flux can be published in a different thread
        .flatMap(integer -> {
            return Mono.fromCallable(() -> {
                 System.out.println("val:" + integer + ", thread:" + Thread.currentThread().getId()); 
                 return integer;
            }).publishOn(Schedulers.parallel()); // <- Each Mono processing every integer can be processed in a different thread
         })
        .repeat()
        .subscribe();

The output becomes:

val:3, thread:16
val:2, thread:15
val:7, thread:20
val:8, thread:13
val:5, thread:18
val:6, thread:19
val:3, thread:17
val:5, thread:19
val:6, thread:20
val:1, thread:15
val:8, thread:14
val:4, thread:18
val:7, thread:13
Source: stackoverflow
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