In today's data-driven world, real-time data processing and analytics have become crucial for businesses to stay competitive. Apache Hudi (Hadoop Upserts and Incremental) is an open-source data management framework that provides efficient data ingestion and real-time analytics on large-scale datasets stored in data lakes. In this blog, we'll explore Apache Hudi with a technical deep dive and Python code examples, using a business example for better clarity.
- Table of Contents:
- Introduction to Apache Hudi
- Key Features of Apache Hudi
- Business Use Case
- Setting Up Apache Hudi
- Ingesting Data with Apache Hudi
- Querying Data with Apache Hudi
- Security and Other Aspects
- Security
- Performance Optimization
- Monitoring and Management
- Conclusion
1. Introduction to Apache Hudi
Apache Hudi is designed to address the challenges associated with managing large-scale data lakes, such as data ingestion, updating, and querying. Hudi enables efficient data ingestion and provides support for both batch and real-time data processing.