```json { "table_name": "Iris", "primary_key": "Id", "candidates": [ { "rank": 0, "partition_key": "Species", "partition_key_label": "primary_identifier", "partition_key_reasoning": "Species has RPUV=50.00 (3 unique values, 50 rows each), providing balanced partitioning for this small dimension table. Top 3 Coverage=100% with equal distribution across three species. Semantically, Species is the natural categorical grouping for iris flower measurements.", "clustering_key": "Id", "clustering_key_label": null, "clustering_key_reasoning": "Id provides deterministic ordering within each species partition. Monotonicity=1.000, perfectly sequential from 1-150. While not required for dimension tables, clustering by Id ensures consistent row ordering for reproducible queries.", "world_line": null, "session_column": null, "confidence": "HIGH", "notes": "This is the classic Iris dataset - a dimension table of flower measurements. Id is the primary key (RPUV=1.00, uniqueness=1.000). Species provides the most meaningful partitioning despite the small size (150 rows), as it creates three balanced partitions of 50 rows each. The measurement columns (SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm) are attributes. Metadata columns (_ingestion_timestamp, _batch_id, _source_file, _source_system) all have RPUV=150.00 (single value) and are not suitable for partitioning." } ] } ```