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Learning Concurrent Programming in Scala

You're reading from   Learning Concurrent Programming in Scala Practical Multithreading in Scala

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Product type Paperback
Published in Feb 2017
Publisher
ISBN-13 9781786466891
Length 434 pages
Edition 2nd Edition
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Author (1):
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Aleksandar Prokopec Aleksandar Prokopec
Author Profile Icon Aleksandar Prokopec
Aleksandar Prokopec
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Table of Contents (11) Chapters Close

Preface 1. Introduction FREE CHAPTER 2. Concurrency on the JVM and the Java Memory Model 3. Traditional Building Blocks of Concurrency 4. Asynchronous Programming with Futures and Promises 5. Data-Parallel Collections 6. Concurrent Programming with Reactive Extensions 7. Software Transactional Memory 8. Actors 9. Concurrency in Practice 10. Reactors

Event streams


In this section, we study the basic data-type that drives most computations in the Reactors framework: an event stream. Event streams represent special program values that can occasionally produce events. Event streams are represented by the Event[T] type.

Semantically, an event stream is very similar to the Observable type, which we saw in Chapter 6, Concurrent Programming with Reactive Extensions. As we will see, the main difference between Observable and Events is that an Observable object can generally be used from different threads, and even emit events across different threads when the observeOn method is used. An Events object, by contrast, can only be used inside the reactor that owns that event stream.

Tip

Never share an event stream between two reactors. An event stream can only be used by the reactor that owns the corresponding channel.

In the following, we show an example event stream called myEvents, which produces events of type String:

val myEvents: Events[String...
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