Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
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

Product type Book
Published in Jan 2022
Publisher Packt
ISBN-13 9781800564930
Pages 342 pages
Edition 1st Edition
Languages
Author (1):
Jan Lukavský Jan Lukavský
Profile icon Jan Lukavský
Toc

Table of Contents (13) Chapters close

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 19 – Implementing RPCParDo in the Python SDK

This task will be a reimplementation of Task 8 from Chapter 3, Implementing Pipelines using Stateful Processing. We will use a stateful DoFn to batch the elements for a defined maximal amount of time. As always, we will restate the problem again for clarity.

Problem definition

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

As in the previous task, we will skip the discussion of the problem's decomposition as we discussed that when we implemented Task 8. Instead, we will jump directly into its implementation using the Python SDK.

Solution implementation

The implementation can be found in chapter6/src/main/python/rpc_par_do.py. It can be broken down into the RPCParDoStateful transform, which is declared...

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 $15.99/month. Cancel anytime