Deck for a workshop with Reactive programming using Spring Webflux. This session was first conducted at the Bangalore Java User Group. Details here: https://www.meetup.com/bangalorejug/events/288770047/

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Reactive Programming
Mritunjay Dubey & Kumar Sankara Iyer

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Table of contents
Setup 03
Threading models and Demo 04
Reactive programming concepts and Spring Webflux 05
Reactive Data types & Operators and hands-on 06
Corner cases, Error handling and hands-on 07
Reactor context demo 10
Demo of end-to-end streams 13
Miscellaneous topics 17
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Setup
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Prerequisites for hands-on
1. Install Java 17 (preferred)
2. Use an IDE like Intellij
3. Install Git (good to have)
4. Install Postman (good to have)
5. Clone the code from
https://github.com/reactive-workshop/reactive-building-blocks
6. Run ./gradlew bootRun
7. Import Reactive-Workshop.postman_collectioninto Postman and run the first
API “Get User By User Id”
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Threading models
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Thread-per-request model
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Drawbacks of the
thread-per-request
model
The thread-per-request model is
neither performant not scalable
Context
switching is
expensive
Threads are
blocked while
I/O is in progress
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A thread takes a
minimum of 1 MB
of stack size
Threads
increase as the
number of
requests

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Event-loop model
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Netty
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A framework to create asynchronous, event-driven applications

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Demo on threading models
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Reactive programming concepts and Spring
Webflux
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Asynchronous
1.
Reactive streams
There are several implementations of the Reactive streams specification - RxJava,
Reactor, Akka streams, RxJavaScript and so on
A standard for asynchronous stream processing
Non-blocking
2.
Backpressure
3.
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Reactive streams - some keywords
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Spring Webflux
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A fully Reactive framework that embraces Functional Reactive Programming

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Reactive Data
types & Operators
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Mono
Mono is a Reactive Streams Publisher that emits at most one item and then terminates
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For eg;

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Flux
Flux is a Reactive Streams Publisher that emits 0 to N elements and then completes
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For eg;

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map
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Transforms a Flux to another
Flux by applying a
synchronous function to
each item

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flatMap
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Flatten the inner publishers
into a single Flux through
merging, allowing them to
interleave

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filter
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Evaluate each source value
against the given predicate

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zip
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Wait for all sources to emit
one element, then combine
these elements. Continue till
any of the sources complete

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Hands-on with
Reactor operators
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Corner cases and
Error handling
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switchIfEmpty
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Switch to an alternative
publisher if this publisher is
empty

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onErrorMap
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Transform a source error to
another error

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onErrorResume
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Subscribe to a fallback
publisher if any error
happens in source

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Hands-on with
error handling
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Reactor context - a demo
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End-to-end streams - a demo
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Miscellaneous
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Reactive
programming is fun!
Building and running on reactive
applications on production requires
Further reading
Learning curve
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Blocking calls
A word on
Testing

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Discussion
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Thankyou
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