Search icon
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Simplifying Data Engineering and Analytics with Delta

You're reading from  Simplifying Data Engineering and Analytics with Delta

Product type Book
Published in Jul 2022
Publisher Packt
ISBN-13 9781801814867
Pages 334 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Anindita Mahapatra Anindita Mahapatra
Profile icon Anindita Mahapatra

Table of Contents (18) Chapters

Preface Section 1 – Introduction to Delta Lake and Data Engineering Principles
Chapter 1: Introduction to Data Engineering Chapter 2: Data Modeling and ETL Chapter 3: Delta – The Foundation Block for Big Data Section 2 – End-to-End Process of Building Delta Pipelines
Chapter 4: Unifying Batch and Streaming with Delta Chapter 5: Data Consolidation in Delta Lake Chapter 6: Solving Common Data Pattern Scenarios with Delta Chapter 7: Delta for Data Warehouse Use Cases Chapter 8: Handling Atypical Data Scenarios with Delta Chapter 9: Delta for Reproducible Machine Learning Pipelines Chapter 10: Delta for Data Products and Services Section 3 – Operationalizing and Productionalizing Delta Pipelines
Chapter 11: Operationalizing Data and ML Pipelines Chapter 12: Optimizing Cost and Performance with Delta Chapter 13: Managing Your Data Journey Other Books You May Enjoy

Handling streaming scenarios

In this section, we will see how to tackle common streaming requirements such as joining a stream with other data, some of which could be a mix of batch and streams; recovering from an intermittent failure scenario, which may involve restarting the stream after a period of inactivity; and handling late-arriving data, among other scenarios.

Joining with other static and dynamic datasets

Joins are a very common operation and streaming datasets are no exception. Very often, they need to be joined with other datasets, usually a slowly-changing dimension dataset to fortify the data for rich analytics. Let's consider an IoT use case where devices are being manufactured in lots and getting registered in a Delta lookup table. As the devices are deployed in the field, they start emitting sensor data that is streaming in nature and comes at a higher velocity. This IoT data needs to be joined with the device's lookup data. Storing device data in Delta...

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}