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Hudi In Action

Welcome to the code repository for the upcoming book "Hudi In Action". This repository contains hands-on examples, tutorials, and code samples that demonstrate Apache Hudi's capabilities for building robust data lakes.

πŸ“– About the Book

"Hudi In Action" is a comprehensive guide to Apache Hudi, covering everything from basic concepts to advanced production patterns. The book provides practical examples and real-world scenarios to help you master Hudi for your data engineering needs.

πŸ—‚οΈ Repository Structure

hudiinaction/
β”œβ”€β”€ chapter02/                          # Getting Started with Hudi
β”‚   β”œβ”€β”€ hudi_pipeline_quickstart.scala  # Comprehensive Hudi tutorial
β”‚   β”œβ”€β”€ trips_0.gz                      # NYC Taxi dataset sample (~1M rows)
β”‚   └── README.md                       # Chapter-specific instructions
└── README.md                           # This file

Each chapter contains its own README with specific learning objectives, setup instructions, and detailed guidance.

πŸ“‹ Prerequisites

Before running the examples, ensure you have:

Software Requirements

  • Apache Spark 3.5+ with Scala 2.12
  • Java 8 or 11
  • Apache Hudi 1.0.2+ (included via Spark packages)

Hardware Requirements

  • At least 4GB RAM available for Spark
  • 2+ CPU cores recommended
  • ~2GB disk space for sample data and tables

πŸš€ Getting Started

  1. Clone this repository
  2. Navigate to the chapter you want to explore
  3. Follow the chapter-specific README for detailed setup instructions
  4. Each chapter is self-contained with its own dataset and examples

🀝 Contributing

Found an issue or want to improve the examples? Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes with clear commit messages
  4. Submit a pull request

πŸ“„ License

This code is provided as supplementary material for "Hudi In Action". Please refer to the book's license terms for usage restrictions.

πŸ“§ Support

For questions about the book or code examples:


Happy learning with Apache Hudi! πŸŽ‰

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