Apache Iceberg Fundamentals

• Familiarity with concepts such as tables, schemas, partitions, and data ingestion
• Basic knowledge of SQL

Audience

• Data engineers
• Data architects
• Data analysts
• Software developers

Apache Iceberg is an open-source table format for large-scale data sets that brings the reliability and simplicity of SQL tables to big data. It was designed to solve the challenges of managing big data in data lakes, which often involve handling complex schemas, large files, and diverse data sources.

This instructor-led, live training (online or onsite) is aimed at beginner-level data professionals who wish to acquire the knowledge and skills necessary to effectively utilize Apache Iceberg for managing large-scale datasets, ensuring data integrity, and optimizing data processing workflows.

By the end of this training, participants will be able to:

• Gain a thorough understanding of Apache Iceberg's architecture, features, and benefits.
• Learn about table formats, partitioning, schema evolution, and time travel capabilities.
• Install and configure Apache Iceberg in different environments.
• Create, manage, and manipulate of Iceberg tables.
• Understand the process of migrating data from other table formats to Iceberg.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Apache Iceberg

• Overview of Apache Iceberg
• Importance and use cases in modern data architecture
• Key features and benefits

Core Concepts

• Iceberg table format and architecture
• Comparison with other table formats
• Partitioning and schema evolution
• Time travel and data versioning

Setting Up Apache Iceberg

• Installation and configuration
• Integrating Iceberg with various data processing engines
• Setting up an Iceberg environment on a local machine

Basic Operations

• Creating and managing Iceberg tables
• Writing to and reading from Iceberg tables
• Basic CRUD operations

Data Migration and Integration

• Migrating data from Hive and other systems to Iceberg
• Integration with BI tools
• Migrating a sample dataset to Iceberg

Optimizing Performance

• Performance tuning techniques
• Optimizing queries and data scans
• Performance optimization in Iceberg

Overview of Advanced Features

• Partition evolution and hidden partitioning
• Table evolution and schema changes
• Time travel and rollback features
• Implementing advanced features in Iceberg

Summary and Next Steps