```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 dimension table with only 21 rows describing the schema of other tables. No column qualifies as a good partition key: Table has RPUV=5.25 with only 4 unique values and 85.71% top-3 coverage (too skewed); Field has RPUV=1.17 with high uniqueness but represents field names (not a natural partitioning dimension). All technical columns (_batch_id, _source_file, etc.) have RPUV=21.00 (single value). For such a small metadata table, partitioning provides no benefit.", "clustering_key": null, "clustering_key_label": null, "clustering_key_reasoning": "No clustering needed for a 21-row metadata table. Natural access pattern is by (Table, Field) composite key for lookups, not range scans.", "world_line": null, "session_column": null, "confidence": "HIGH", "notes": "This is a data dictionary / schema metadata table describing fields in accounts, products, sales_teams, and b2b_sales_funnel_pipeline. The composite key (Table, Field) uniquely identifies each row. With only 21 rows and no temporal or analytical partitioning needs, this table should remain unpartitioned for simplicity and performance." } ] } ```