Flight of the Flux - Speaker Deck

Flight of the Flux

by Simon Baslé

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Flight of the Flux a look at Reactor's execution model

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Flight of the Flux a look at Reactor's execution model @simonbasle

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What we'll learn

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Nothing happens until you subscribe, Assembly time vs Execution time

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Nothing happens until you subscribe, Assembly time vs Execution time Cold or Hot?

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Nothing happens until you subscribe, Assembly time vs Execution time Cold or Hot? Concurrent agnostic

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Cold or Hot? Concurrent agnostic Schedulers, PublishOn vs SubscribeOn Nothing happens until you subscribe, Assembly time vs Execution time

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Cold or Hot? Concurrent agnostic Schedulers, PublishOn vs SubscribeOn Work Stealing Nothing happens until you subscribe, Assembly time vs Execution time

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Cold or Hot? Concurrent agnostic Schedulers, PublishOn vs SubscribeOn Work Stealing Operator Fusion Nothing happens until you subscribe, Assembly time vs Execution time

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Cold or Hot? Concurrent agnostic Schedulers, PublishOn vs SubscribeOn Work Stealing Operator Fusion Nothing happens until you subscribe, Assembly time vs Execution time

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Publisher Subscriber

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...

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...

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...

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Subscription

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Nothing Happens until you subscribe Assembly time

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Nothing happen until you subscribe

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Assembly time

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this.myFlux = Flux.just("foo") .map(String::length); MyTest#init()

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Execution time

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Execution time Subscription

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this.myFlux .subscribe(); MyTest#test()

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what would I see in a stack trace?

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java.lang.ArithmeticException: / by zero at reactor.core.publisher.FluxMapFuseable$MapFuseableSubscriber.onNext(FluxMapFuseable.java:107) at reactor.core.publisher.FluxMapFuseable$MapFuseableSubscriber.onNext(FluxMapFuseable.java:115) at reactor.core.publisher.FluxJust$WeakScalarSubscription.request(FluxJust.java:99) at reactor.core.publisher.FluxMapFuseable$MapFuseableSubscriber.request(FluxMapFuseable.java:156) at reactor.core.publisher.FluxMapFuseable$MapFuseableSubscriber.request(FluxMapFuseable.java:156) at reactor.core.publisher.BlockingSingleSubscriber.onSubscribe(BlockingSingleSubscriber.java:49) at reactor.core.publisher.FluxMapFuseable$MapFuseableSubscriber.onSubscribe(FluxMapFuseable.java:90) at reactor.core.publisher.FluxMapFuseable$MapFuseableSubscriber.onSubscribe(FluxMapFuseable.java:90) at reactor.core.publisher.FluxJust.subscribe(FluxJust.java:70) at reactor.core.publisher.FluxMapFuseable.subscribe(FluxMapFuseable.java:63) at reactor.core.publisher.FluxMapFuseable.subscribe(FluxMapFuseable.java:63) at reactor.core.publisher.Flux.subscribe(Flux.java:6873) at mycode.test(MyTest.java:xx)

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checkpoint()

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Hot or Cold ?

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Cold publisher

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always true... until it's false " Nothing happen until you subscribe "

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Hot publisher

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Concurrent Agnostic

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do I have to accept a particular execution model?

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No, we provide tools to ﬁne tune

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But, frameworks & libraries built on top might be opinionated

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what about time operators?

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...they do need to change threads

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Schedulers & how to switch threads

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Scheduler abstraction

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, part part

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publishOn

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Flux.op1.op2.publishOn.op3.op4 .subscribe

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1 2 Flux.op1.op2.publishOn.op3.op4 .subscribe

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Thread calling subscribe() is where data ﬂows initially 1

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After publishOn data ﬂows in Thread 2 2

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subscribeOn

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Flux.op1.op2 .subscribeOn .op3.op4 .subscribe

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2 Flux.op1.op2 .subscribeOn .op3.op4 .subscribe 1

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subscribeOn() changes where sequence subscription happens... 1

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... which is also where data ﬂows initially 2

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and the two together?

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Flux .op1 .subscribeOn .op2 .op4 .subscribe( v -> doSomething(v)) .publishOn

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Flux .op1 .subscribeOn .op2 .op4 .subscribe( v -> doSomething(v)) .publishOn

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Flux .op1 .subscribeOn .op2 .op4 .subscribe( v -> doSomething(v)) .publishOn 1 2 3 4

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Work Stealing

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so where do (most) operators run, again?

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publishOn

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what is work stealing?

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1 operator that combines data coming from 2 threads

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shared queue, drain loop

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offer

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offer work

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offer offer work

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offer offer work steal exit

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offer offer work steal exit

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offer offer work steal exit work

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offer offer work steal exit work exit

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Operator Fusion

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macro fusion

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a.then(b).then(c).then(d)

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a.then(b,c,d)

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micro fusion

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a.map(->).map(->).filter(->)

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a.map(->).map(->).filter(->)

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a.map(->).map(->).filter(->) bounded queues (for backpressure)

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a.map(->).map(->).filter(->)

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a.map(->).map(->).filter(->) single transverse bounded queue

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Questions?

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Thanks!

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