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

Product type Paperback

Published in Jan 2024

Publisher Packt

ISBN-13 9781804612583

Length 300 pages

Edition 1st Edition

Languages

Scala

Concepts

Data Engineering

Authors (3):

Rupam Bhattacharjee

David Radford

Eric Tome

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Table of Contents (21) Chapters

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

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Introducing the Spark UI

At its core, the Spark UI is a web-based interface that provides a comprehensive view of the internal workings of your Spark application. It offers detailed information about various aspects of your application’s execution, from a high-level overview down to the specifics of individual tasks and stages. The Spark UI is an invaluable tool for diagnosing bottlenecks, identifying resource utilization, and gaining a deeper understanding of the runtime behavior of your Spark jobs. It is also an integral part of the Spark ecosystem as it’s designed to give you unparalleled visibility into the execution of your Spark applications. Whether you’re working on a small cluster or a sprawling data center, the Spark UI offers a unified interface to monitor, analyze, and optimize the performance of your Spark workloads.

Let’s learn how to navigate the Spark UI.