Synopsis
A friendly, framework-agnostic tutorial that will help you grok how streaming systems work—and how to build your own!
In Grokking Streaming Systems you will learn how to:
Implement and troubleshoot streaming systems
Design streaming systems for complex functionalities
Assess parallelization requirements
Spot networking bottlenecks and resolve back pressure
Group data for high-performance systems
Handle delayed events in real-time systems
Grokking Streaming Systems is a simple guide to the complex concepts behind streaming systems. This friendly and framework-agnostic tutorial teaches you how to handle real-time events, and even design and build your own streaming job that’s a perfect fit for your needs. Each new idea is carefully explained with diagrams, clear examples, and fun dialogue between perplexed personalities!
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Streaming systems minimize the time between receiving and processing event data, so they can deliver responses in real time. For applications in finance, security, and IoT where milliseconds matter, streaming systems are a requirement. And streaming is hot! Skills on platforms like Spark, Heron, and Kafka are in high demand.
About the book
Grokking Streaming Systems introduces real-time event streaming applications in clear, reader-friendly language. This engaging book illuminates core concepts like data parallelization, event windows, and backpressure without getting bogged down in framework-specific details. As you go, you’ll build your own simple streaming tool from the ground up to make sure all the ideas and techniques stick. The helpful and entertaining illustrations make streaming systems come alive as you tackle relevant examples like real-time credit card fraud detection and monitoring IoT services.
What's inside
Implement and troubleshoot streaming systems
Design streaming systems for complex functionalities
Spot networking bottlenecks and resolve backpressure
Group data for high-performance systems
About the reader
No prior experience with streaming systems is assumed. Examples in Java.
About the author
Josh Fischer and Ning Wang are Apache Committers, and part of the committee for the Apache Heron distributed stream processing engine.
Table of Contents
PART 1 GETTING STARTED WITH STREAMING
1 Welcome to Grokking Streaming Systems
2 Hello, streaming systems!
3 Parallelization and data grouping
4 Stream graph
5 Delivery semantics
6 Streaming systems review and a glimpse ahead
PART 2 STEPPING UP
7 Windowed computations
8 Join operations
9 Backpressure
10 Stateful computation
11 Wrap-up: Advanced concepts in streaming systems
About the Author
Josh Fischer is an Apache Committer, and part of the project management committee for the Apache Heron distributed stream processing engine. Josh is a software engineer at Scotcro and has worked with moving large datasets in real time for organizations such as 1904labs and Bayer.
Ning Wang is an Apache Committer, and part of the project management committee for the Apache Heron distributed stream processing engine. Ning is also a software engineer at Amplitude building real-time data pipelines. He was a key contributor of Apache Heron in Twitter’s Real-time Compute team.
"About this title" may belong to another edition of this title.
