Iceberg Foreign Table
Apache Iceberg is an open table format designed for large-scale data lakes, providing ACID transactions, schema evolution, and time travel capabilities. This guide covers integrating Iceberg tables with Tacnode through REST Catalog APIs.
Apache Iceberg Overview
Apache Iceberg provides enterprise-grade table format capabilities for data lakes:
Key Features
Feature | Benefit | Use Case |
---|---|---|
ACID Transactions | Data consistency guarantees | Concurrent operations, data integrity |
Schema Evolution | Non-breaking schema changes | Adding columns, data type changes |
Time Travel | Query historical data states | Audit trails, data recovery |
Partition Evolution | Change partitioning without rewrites | Performance optimization over time |
Hidden Partitioning | Automatic partition management | Simplified queries, better performance |
Catalog Types
Iceberg supports multiple catalog implementations:
- REST Catalog: HTTP-based catalog service
- Hive Metastore: Traditional Hive-compatible catalog
- AWS Glue: Managed AWS catalog service
- Hadoop: Filesystem-based catalog
REST Catalog Integration
Install Iceberg FDW Extension
Create Iceberg Foreign Server
Configure Authentication
Authentication
Schema Management
Import Iceberg Schemas
Best Practices
Best Practices Summary
- Use REST Catalog for scalable metadata management
- Enable time travel for audit trails and data recovery
- Implement proper partitioning for large datasets
- Monitor schema evolution and plan for backward compatibility
- Use materialized views for complex analytical queries
- Implement data quality checks at regular intervals
- Plan snapshot retention policies to control storage costs
- Use appropriate batch sizes for bulk operations
Limitations
- Some advanced Iceberg features may require specific catalog implementations
- Write performance depends on catalog and storage configuration
- Schema evolution capabilities vary by deployment setup
- Snapshot cleanup requires careful planning to avoid data loss
- Cross-catalog operations are not supported
This comprehensive approach to Apache Iceberg integration enables you to leverage advanced table format capabilities while maintaining optimal performance and data governance in your data lake architecture.