```json { "table_name": "quality_issues", "primary_key": "id", "candidates": [ { "rank": 0, "partition_key": "id", "partition_key_label": "primary_identifier", "partition_key_reasoning": "RPUV = 1.00 (all unique), uniqueness = 1.000, monotonicity = 1.000. This is the primary identifier for quality issues. While RPUV=1 is typically poor for partitioning (one file per row), dimension tables are often small reference tables where this is acceptable. With only 417 rows, this table is small enough that partitioning is not critical.", "clustering_key": null, "clustering_key_label": null, "clustering_key_reasoning": "Dimension tables typically do not require internal sorting. No natural ordering axis exists for quality issue records.", "world_line": null, "session_column": null, "confidence": "HIGH", "notes": "This is a dimension table cataloging quality issues detected during data profiling. The id column is the unique identifier per the classification. The table is small (417 rows) and serves as a reference/lookup table. The _ingestion_timestamp, _batch_id, _source_file, and _source_system columns are all constant (RPUV=417), indicating this is a single-batch snapshot. jobs_id (RPUV=3.59) could theoretically be used for partitioning by job, but as a dimension table, the primary_identifier approach is more appropriate." } ] } ```