trino-iceberg-best-practices

What problem does it solve?

This Skill helps you design and operate production Apache Iceberg tables queried via Trino by preventing common performance and maintenance pitfalls like poor partition pruning, small-file bloat, inefficient layouts, and unmanageable snapshot growth.

Core Features & Use Cases

• Production Iceberg DDL blueprint: Specifies storage format, compression, format_version, hidden partitioning transforms, and within-file sorting for better pruning and execution efficiency.
• Maintenance & correctness operations: Covers optimize/compaction, manifest optimization, snapshot expiry, orphan file removal, and safe snapshot/time-travel workflows.
• Evolution & data lifecycle: Guides schema evolution, partition evolution, and DML patterns (INSERT/UPDATE/DELETE/MERGE) aligned with Iceberg requirements and Trino capabilities.
• Performance tuning diagnostics: Recommends ANALYZE usage for CBO and shows how to inspect metadata tables ($snapshots, $files, $partitions, $history) to validate file sizing and commit behavior.

Quick Start

Ask an AI to propose a production-ready Trino Iceberg table DDL for a daily partitioned orders dataset and include an operational maintenance schedule with snapshot retention and compaction settings.