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Building Big Data Pipelines with Apache Beam

You're reading from Building Big Data Pipelines with Apache Beam

Product type Book

Published in Jan 2022

Publisher Packt

ISBN-13 9781800564930

Pages 342 pages

Edition 1st Edition

Languages

Concepts

Data Processing

Author (1):

Jan Lukavský

Table of Contents (13) Chapters

Preface

1. Section 1 Apache Beam: Essentials

2. Chapter 1: Introduction to Data Processing with Apache Beam

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 6 – Using an external service for data augmentation

All of the tasks we solved so far in the previous chapter had all of their data readily available in the input PCollection object. That might not be the case in all situations. Imagine a situation in which you need to augment your input data with some metadata that is located behind an external service. This external service is accessible via a Remote Procedure Call (RPC), as illustrated in the following figure:

Figure 3.1 – Augmenting data with an external service

We feed our input data to a (stateless) operation, which performs an RPC call for each input element (possibly doing some caching) and uses this outcome to somehow modify the input element and output (or discard) it to downstream processing. From this description, we will create a definition of the task problem.

Defining the problem

Given an input stream of lines of text (coming from Apache Kafka) and an RPC service that...

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Authors (1)

Jan Lukavský

Jan Lukavský is a freelance big data architect and engineer who is also a committer of Apache Beam. He is a certified Apache Hadoop professional. He is working on open source big data systems combining batch and streaming data pipelines in a unified model, enabling the rise of real-time, data-driven applications.

See other products by Jan Lukavský

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