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Study mode:
on
1
Introduction
2
What is a Stream?
3
What is a collection?
4
User Expectations
5
Unexpected: observed sequence depends on
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java.util.stream
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Streams vs. Collections
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Possible Solutions
9
The Four Horsemen of Reactive
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Origin and motivation
11
Collaboration between Engineers
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Goals
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Reactive Streams
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A Data Market using Supply & Demand
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Dynamic Push-Pull
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Explicit Demand: One-to-many
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Explicit Demand: Many-to-one
18
The Meat: Java
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The dessert: Java
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How does it Connect?
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How does it Flow?
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How does it Complete?
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Akka Actors
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Canonical papers
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Opportunity: API
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Opportunity: Self-tuning back pressure
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Opportunity: Operation Fusion
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Opportunity: Operation Elision
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Opportunity: Execution optimizations
30
Opportunity: Distributed Streams
31
Outro: How do I get my hands on this?
Description:
Explore stream-based programming and its potential to unify IO with functional programming in this 54-minute conference talk from GOTO Aarhus 2014. Dive into Akka Streams, an asynchronous library with non-blocking back pressure built on top of the Akka Actor Model. Learn about the Flow API, Flow Materialization, and the implications of non-blocking back pressure for fan-in and fan-out scenarios. Discover the concepts of collections and streams, user expectations, and unexpected behaviors in observed sequences. Examine possible solutions, including the Four Horsemen of Reactive and Reactive Streams. Understand the goals and motivations behind these technologies, and explore opportunities for API design, self-tuning back pressure, operation fusion and elision, execution optimizations, and distributed streams. Gain insights into Akka Actors and canonical papers in the field. By the end of the talk, acquire knowledge on how to get hands-on experience with these cutting-edge technologies.

How I Learned to Stop Worrying and Love the Flow

GOTO Conferences
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