Java Streams vs Reactive Streams: Which, When, How, and Why? by Venkat Subramaniam

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Java 8 introduced Streams and Java 9 now has Reactive API. Which one should we choose, when should we choose them, why, and how to use one vs. the other. This session will answer all those questions, by diving deep into the APIs using live code examples.

Venkat Subramaniam
From Agile Developer, Inc.

He has trained and mentored thousands of software developers in the US, Canada, Europe, and Asia, and is a regularly-invited speaker at several international conferences. Venkat helps his clients effectively apply and succeed with sustainable agile practices on their software projects.

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Created a short summary for my own use:

In the context of imperative programming:

1. List-based functional programming is eagerly evaluated.
2. Stream() introduced in Java 8 and is the seam showing we're not programming imperatively anymore. Is it required, though?
a. imperative - what and how
b. declarative - what and *not* how + higher order functions = FP. Code reads like the problem statement, through "internal iteration"/ "iteration on autopilot"
Mutability is OK, but shared mutability is not.
3. In OOP we encapsulate moving parts - in FP, we eliminate them.
4. Is stream API slow - you don't want a faster bicycle, but a rocket - EASIER TO PARALLELIZE
5. List is bucket, Stream is pipeline. You don't store water in a pipeline, you just move it through there.
6. Functional composition (builder pattern) is essential.
7. Lazy evaluation example - removing the terminal (collect) method - functions not being called anymore, as result not needed.
8. Many languages give programming pattern, such as Groovy, but laziness not there, as it depends on implementation.


Limitations of streams:
1. Single use only. Example where a stream is assigned to a variable, printed and then used with different filter condition. Result: IllegalStateException: stream has been operated on or closed.
a. Concept: streams like QTips - use once and throw away.
2. Not possible to fork in the middle. Only a single terminal operation.
3. How do you deal with exceptions: sorry :(. Exception handling is an imperative-style idea: call a function, which calls a function, etc. and destroys your callstack.
a. Scala has Mono monads and Either objects - provides safe handling, which is propagated and used in downstream stages. Lacks cohesion!
b. Still good luck - we want pure functions and exceptions normally come from impurity.


Reactive systems:

1. Came out of Microsoft research, but just a new name for old concept - system that reacts to stimuli
2. Four pillars of reactive programming:
a. Elasticity
b. Message-driven
c. Responsive
d. Resilience - circuit breakers built in, partial access to application
3. Close to the 80's concept of dataflow computing: d → f → d →f
a. Instructions ready to fire when the data is available
b. Serverless computing (AWS Lambda) == dataflow programming. At the minute computation is ready and prepared it can run on ANY server with predefined affinity
4. Reactive programming is FP++ - builds on lazy evaluation and functional composition
a. Example with Flowable and subscribe on it
5. Both Java Streams and Reactive ones push data, regular iterators pull. They are similar to Observable, you register to it and it pushes data to you.
6. Both can return 0, 1 or more data.
7. Java 8 Streams deal only with data. RS contain three channels (Data, Err, Complete). In RS error is just another form of data.
8. RS are asynchronous, so you are not locked into parallelism (sync).
9. RS can handle consumer back-pressure.
10. Multiple subscribers in RS, where single pipeline in Java Streams
11. Interface differences:
a. Reactive Stream:
- Publisher
- Subscriber
- Subscription - session between emitter and subscriber, can hold context
- Processor - publisher + subscriber
- Implementations: RxJava, Akka, Reactor (Spring 5), RSocket
b. Java reactive streams - same interface, since Java 9 - in the java.util.concurrent.Flow.* class

evgenienchev
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Hello from Brazil, I just imagine how amazing could be a class from Dr. Venkat at University of Houston. Lucky students.

douglaaaaaas
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39:00 reactive programming
41:00 reactive application
42:30 reactive systems
46:40 reactive programming principles
1:01:00 reactive streams
1:01:00 data flow computing
1:07:54 channels of communication
1:13:17 similarities with streams and differences
1:27:00 circuit breaker
1:39:30 non blocking and back pressure
1:51:00 multiple subscribers
2:00:00 reactive streams api
2:01:44 publisher
2:02:36 subscriber
2:03:00 subscription
2:05:50 processors
2:08:24 reactive libraries
2:10:45 java 9 reactive streams api

m.m.
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One thing about Venkat’s talks - every time I watch I learn something new. Thanks a million for the talk

NiranjanNanda
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He is just amazing. Pure 150 mins of infotainment .

Max-zfot
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If Teaching is an art, this person is the Piccaso of it. Thanks !!!

sandaruwanp
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What a great lecture. When I saw the video was 2.5 hours I figured I would skim over in about 10 minutes on the off chance I would see something interesting but instead I am enjoying the entire thing. Fantastic speaker.

ecco
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40:20 "...every 10 year, we give a new name to what we already do and get really excited about it..."

samratdr
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5 years on from the video, and what he says hold true! Lots of libraries, and lots of usage of reactive programming currently.

jinuvijay
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Venkat sounds like... you're trying to figure out the perfect playback speed and you change it all the time. Great talk!

andrapravai
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If you wanna skip the Java 8, streams and Functional and imperative programming introduction and go straight to Reactive stuff, this is the moment, go to 39:00

andersonmontanez
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Teaching at its best.. simple...loved the energy..thank you for sharing this video..

maclovesgeet
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nice talk. Thank you for uploading conference talks

relaxsightme
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The explanations for some of the concepts were quite illuminating. Thanks!

ylikjek
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Thanks again for providing inspiring and great talk of the Reactive Streams concept. Hats off to your relentless contribution to the Java community. You are a truly Inspiring tech talker.

nagamohank
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@37 Exceptions. You can be proactive by using a filter to eliminate problematic data from stream. This works for many kinds of cases, e.g. if the list of numbers in the example contained a null.

tdrake
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Good presentation, lot of words at x1.25. A plus for tackling the topic of exception handling support in streams API or rather lack of it.

ryumak
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Once you start listening to Venkat, you just can't stop yourself to keep listening. And after completing this one you will be searching for more such talks by Venkat. I just wonder, people will even be listening to him if he speaks any useless words, thats the aura & way of presentation he has got :)

nitinagrawal
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I think in spring 5 it’s not Flow, it’s Flux

And it’s not part of spring 5, it’s part of project reactor and spring 5 uses it for webflux

NiranjanNanda
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How to get that background for. Textmate

ambarishyt