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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

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781800564930
Length 342 pages
Edition 1st Edition
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Author (1):
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Jan Lukavský Jan Lukavský
Author Profile Icon Jan Lukavský
Jan Lukavský
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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

Task 16 – Implementing SQLSportTrackerMotivation

In this task, we will explore the benefits that SQL DSL brings us when it comes to more complex pipelines that are composed of several aggregations, joins, and so on. Again, as a recap, let's restate the problem definition.

Problem definition

Given a GPS location stream per workout (the same as in the previous task), create another stream that would contain information if the runner increased or decreased pace in the past minute by more than 10% compared to the average pace over the last 5 minutes. Again, use SQL DSL as much as possible.

The test and deployment are the same as in the corresponding SportTracker task, so we will skip this here. Instead, we will demonstrate how SQL (and schemas) can help us when we are dealing with joins – which is what we did when we were implementing our SportTrackerMovation example. So, let's reimplement that as well!

Problem decomposition discussion

In the original...

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