Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Building Big Data Pipelines with Apache Beam

You're reading from   Building Big Data Pipelines with Apache Beam Use a single programming model for both batch and stream data processing

Arrow left icon
Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781800564930
Length 342 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
Jan Lukavský Jan Lukavský
Author Profile Icon Jan Lukavský
Jan Lukavský
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Section 1 Apache Beam: Essentials
2. Chapter 1: Introduction to Data Processing with Apache Beam FREE CHAPTER 3. Chapter 2: Implementing, Testing, and Deploying Basic Pipelines 4. Chapter 3: Implementing Pipelines Using Stateful Processing 5. Section 2 Apache Beam: Toward Improving Usability
6. Chapter 4: Structuring Code for Reusability 7. Chapter 5: Using SQL for Pipeline Implementation 8. Chapter 6: Using Your Preferred Language with Portability 9. Section 3 Apache Beam: Advanced Concepts
10. Chapter 7: Extending Apache Beam's I/O Connectors 11. Chapter 8: Understanding How Runners Execute Pipelines 12. Other Books You May Enjoy

Understanding windowing semantics in depth

In Chapter 1, Introducing Data Processing with Apache Beam, we introduced the basic types of window functions. To recap, we defined the following:

  • Fixed windows
  • Sliding windows
  • Global window
  • Session windows

We also defined two basic types of windows: key-aligned and key-unaligned. The first three types (fixed, sliding, and global) are key-aligned, and session windows are key-unaligned (as in session windows, each window can start and end at different times for different keys). However, what we skipped in Chapter 1, Introduction to Data Processing with Apache Beam, was the fact that we can define completely custom windowing logic.

The Window.into transform accepts a generic WindowFn instance, which defines the following main methods:

  1. The assignWindows method, which assigns elements into a set of window labels.
  2. The isNonMerging method, which tells the runner whether the WindowFn instance defines merging...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime