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Iceberg Foreign Table

Learn how to integrate Apache Iceberg with Tacnode using foreign tables, enabling advanced table format capabilities for data lakes.

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

The following instructions are written to be run from the psql command line

-- Install Apache Iceberg foreign data wrapper
CREATE EXTENSION IF NOT EXISTS iceberg_fdw;

-- Verify installation
SELECT extname, extversion 
FROM pg_extension 
WHERE extname = 'iceberg_fdw';

-- Check FDW capabilities
\des+ iceberg_fdw

Create Iceberg Foreign Server

-- Production Iceberg REST Catalog
CREATE SERVER iceberg_production FOREIGN DATA WRAPPER iceberg_fdw
OPTIONS (
    iceberg_rest_catalog_endpoint 'https://iceberg-catalog.company.com/api/catalog',
    catalog 'production_catalog'
);

-- Development catalog
CREATE SERVER iceberg_dev FOREIGN DATA WRAPPER iceberg_fdw
OPTIONS (
    iceberg_rest_catalog_endpoint 'http://localhost:8181/api/catalog',
    catalog 'dev_catalog'
);

Configure Authentication

Authentication

-- authentication headers
CREATE USER MAPPING FOR current_user SERVER iceberg_tenant_a
OPTIONS (
    token 'principal:data-reader;realm:company-realm'
);

Schema Management

Import Iceberg Schemas

-- Import entire namespace
IMPORT FOREIGN SCHEMA "sales_analytics"
FROM SERVER iceberg_production
INTO sales_schema;

-- Import specific tables
IMPORT FOREIGN SCHEMA "customer_data"
    LIMIT TO (customer_profiles, purchase_history, loyalty_metrics)
FROM SERVER iceberg_production
INTO customer_schema;

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.