Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Data Engineering with Scala and Spark

You're reading from   Data Engineering with Scala and Spark Build streaming and batch pipelines that process massive amounts of data using Scala

Arrow left icon
Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781804612583
Length 300 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Rupam Bhattacharjee Rupam Bhattacharjee
Author Profile Icon Rupam Bhattacharjee
Rupam Bhattacharjee
David Radford David Radford
Author Profile Icon David Radford
David Radford
Eric Tome Eric Tome
Author Profile Icon Eric Tome
Eric Tome
Arrow right icon
View More author details
Toc

Table of Contents (21) Chapters Close

Preface 1. Part 1 – Introduction to Data Engineering, Scala, and an Environment Setup
2. Chapter 1: Scala Essentials for Data Engineers FREE CHAPTER 3. Chapter 2: Environment Setup 4. Part 2 – Data Ingestion, Transformation, Cleansing, and Profiling Using Scala and Spark
5. Chapter 3: An Introduction to Apache Spark and Its APIs – DataFrame, Dataset, and Spark SQL 6. Chapter 4: Working with Databases 7. Chapter 5: Object Stores and Data Lakes 8. Chapter 6: Understanding Data Transformation 9. Chapter 7: Data Profiling and Data Quality 10. Part 3 – Software Engineering Best Practices for Data Engineering in Scala
11. Chapter 8: Test-Driven Development, Code Health, and Maintainability 12. Chapter 9: CI/CD with GitHub 13. Part 4 – Productionalizing Data Engineering Pipelines – Orchestration and Tuning
14. Chapter 10: Data Pipeline Orchestration 15. Chapter 11: Performance Tuning 16. Part 5 – End-to-End Data Pipelines
17. Chapter 12: Building Batch Pipelines Using Spark and Scala 18. Chapter 13: Building Streaming Pipelines Using Spark and Scala 19. Index 20. Other Books You May Enjoy

Working with GitHub

There are many different ways to interact with GitHub. You can use an IDE’s interface or extensions, a web user interface, or a command-line interface (CLI). We’ll focus on the Git and GitHub CLIs for this portion of the book.

The Git CLI, or git, is the command-line tool that interacts directly with the Git version control system. It provides a set of commands to manage the entire lifecycle of a Git repository, such as creating repositories, initializing a new repository, cloning repositories, managing branches, committing changes, merging branches, and more. It is installed on your local machine and can be used with any Git-compliant repository.

The GitHub CLI, or gh, is a command-line tool provided by GitHub that extends Git’s functionality with additional features and allows you to interact with GitHub repositories directly from the command line. It also offers commands for creating repositories; cloning repositories; managing pull...

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 €18.99/month. Cancel anytime