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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

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781804612583
Length 300 pages
Edition 1st Edition
Languages
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Authors (3):
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Rupam Bhattacharjee Rupam Bhattacharjee
Author Profile Icon Rupam Bhattacharjee
Rupam Bhattacharjee
David Radford David Radford
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David Radford
Eric Tome Eric Tome
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Eric Tome
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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

Running static code analysis

Static code analysis is a debugging method that is performed without running the code. With application security taking center stage, it is very important to catch potential vulnerabilities early in the development phase and address them as you build your application code. Static code analysis helps developers catch issues such as the following:

  • Coding standard violations
  • Security vulnerabilities
  • Programming errors

There are several tools available for static code analysis. For this book, we are going to look at SonarQube, which can analyze over 30 different programming languages and is one of the most widely adopted tools for static code analysis.

Installing SonarQube locally

The easiest way to install SonarQube is to launch it as a Docker container using the following command:

docker run -d --name sonarqube -e SONAR_ES_BOOTSTRAP_CHECKS_DISABLE=true -p 9000:9000 sonarqube:latest

Once installed, open http://localhost:9000...

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