```json { "table_name": "jobs", "primary_key": "job_id", "candidates": [ { "rank": 0, "partition_key": "job_id", "partition_key_label": "primary_identifier", "partition_key_reasoning": "job_id is the unique identifier for each job record with RPUV=1.00, uniqueness=1.000, and 321 unique values across 321 rows. It serves as the natural primary key for this dimension table.", "clustering_key": null, "clustering_key_label": null, "clustering_key_reasoning": "Dimension tables typically do not require clustering keys as they are reference tables organized by their primary identifier.", "world_line": null, "session_column": null, "confidence": "HIGH", "notes": "This is a dimension table tracking job metadata. The job_id is the definitive unique identifier. Time columns (started_at, finished_at, created_at, updated_at) are event_time attributes of each job but do not define the table's organization — they describe when job state transitions occurred. The dataset_id (RPUV=2.94, 109 unique values) represents which dataset each job processes, but partitioning by dataset_id would be an alternative perspective only if analyzing jobs from a dataset-centric view." } ] } ```