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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 8 – Batching queries to an external RPC service with defined batch sizes

Let's suppose that our RPC server works best when it processes about 100 input words in a batch. A real-world requirement would probably look different and would be the result of measurements rather than an arbitrary number. However, for the present discussion, let's suppose that this performance characteristic is given. We can then summarize the task as follows.

Defining the problem

Use a given RPC service to augment data in an input stream using batched RPCs with batches of a size of about K elements. Also, resolve the batch after a time of (at most) T to avoid a (possibly) infinitely long wait for elements in small batches.

As we can see, we extended the definition of the problem with the introduction of a parameter, T, which will guard the time for which we can buffer the elements waiting for more data.

Discussing the problem decomposition

As already mentioned, we cannot...

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