```json { "table_name": "data_dictionary", "primary_key": "Table,Field", "candidates": [ { "rank": 0, "partition_key": null, "partition_key_label": null, "partition_key_reasoning": "This is a metadata table with only 21 rows describing the schema of other tables. Table column has RPUV=5.25 with only 4 unique values (85.71% top-3 coverage), making it unsuitable for partitioning. Field column has RPUV=1.17 with high uniqueness (0.857) but only 18 unique values across 21 rows. For such a small reference table (21 rows), partitioning provides no performance benefit and would create unnecessary overhead. Best stored as a single small file.", "clustering_key": null, "clustering_key_label": null, "clustering_key_reasoning": "No clustering needed for a 21-row metadata table. Natural ordering by (Table, Field) composite primary key is sufficient for lookups and joins.", "world_line": null, "session_column": null, "confidence": "HIGH", "notes": "This is a schema metadata table (data dictionary) with 21 rows describing fields across 4 tables (accounts, products, sales_pipeline, sales_teams). The composite key (Table, Field) uniquely identifies each row. As a small, static reference table, it requires no partitioning or clustering - it should remain as a single file for efficient full-table scans and metadata lookups. The _ingestion_timestamp and other underscore-prefixed columns are ETL metadata, not business keys." } ] } ```