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Course Outline
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
Requirements
- Familiarity with concepts such as tables, schemas, partitions, and data ingestion.
- Basic knowledge of SQL.
Audience
- Data engineers.
- Data architects.
- Data analysts.
- Software developers.
14 Hours
Testimonials (1)
Hands on exercises. Class should have been 5 days, but the 3 days helped to clear up a lot of questions that I had from working with NiFi already
