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Data Engineering with Scala and Spark

You're reading from  Data Engineering with Scala and Spark

Product type Book
Published in Jan 2024
Publisher Packt
ISBN-13 9781804612583
Pages 300 pages
Edition 1st Edition
Languages
Authors (3):
Eric Tome Eric Tome
Profile icon Eric Tome
Rupam Bhattacharjee Rupam Bhattacharjee
Profile icon Rupam Bhattacharjee
David Radford David Radford
Profile icon David Radford
View More author details

Table of Contents (21) Chapters

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

Introducing CI/CD and GitHub

One of the most common platforms for implementing CI/CD and collaborating on code is GitHub. GitHub and its ecosystem provide a variety of tools to manage your data engineering project from development to deployment to production.

In this section, let’s cover how CI and CD work on GitHub.

Understanding Continuous Integration (CI)

The core concept of CI on GitHub revolves around continuously integrating code changes from multiple contributors into a shared repository. Whenever developers push changes to the repository, automated build and test processes are triggered. This enables teams to detect integration issues, conflicts, and errors early on, promoting a more stable and coherent code base. Through the use of GitHub Actions or third-party CI tools such as Jenkins or CircleCI, developers can define custom workflows to automate the build and test stages, ensuring code integrity. We will cover GitHub Actions later in this chapter.

Understanding...

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