Spark Scala Real-World Coding Frameworks and Testing

Spark Scala Framework, Hive, IntelliJ, Maven, Logging, Exception Handling, log4j, ScalaTest, JUnit

This course bridges the gap between academic learning and real-world application, preparing you for an entry-level Big Data Spark Scala Developer role. You'll gain hands-on experience with industry best practices, essential tools, and frameworks used in Spark development.

What You’ll Learn:

• Spark Scala Coding Best Practices – Write clean, efficient, and maintainable code

• Logging – Implement logging using Log4j and SLF4J for debugging and monitoring

• Exception Handling – Learn best practices to handle errors and ensure application stability

• Configuration Management – Use Typesafe Config for managing application settings

• Development Setup – Work with IntelliJ and Maven for efficient Spark development

• Local Hadoop Hive Environment – Simulate a real-world big data setup on your machine

• PostgreSQL Integration – Read and write data to a PostgreSQL database using Spark

• Unit Testing – Test Spark Scala applications using JUnit, ScalaTest, FlatSpec & Assertions

• Building Data Pipelines – Integrate Hadoop, Spark, and PostgreSQL for end-to-end workflows

• Bonus – Set up Cloudera QuickStart VM on Google Cloud Platform (GCP) for hands-on practice

Prerequisites:

• Basic programming knowledge

• Familiarity with databases

• Introductory knowledge of Big Data & Spark

This course provides practical, hands-on training to help you build and deploy real-world Spark Scala applications. By the end of this course, you’ll have the confidence and skills to build, test, and deploy Spark Scala applications in a real-world big data environment.

This course uses high-quality AI-generated text-to-speech narration to complement the powerful visuals and enhance your learning experience.