```json { "table_name": "ai_job_dataset", "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 with RPUV=1.00, uniqueness=1.000, and 15,000 unique values for 15,000 rows. Each job posting has a distinct ID (AI00001, AI00002, etc.). This is the natural primary key for a dimension table of job postings.", "clustering_key": null, "clustering_key_label": null, "clustering_key_reasoning": "Dimension tables typically do not require clustering keys as they are reference data looked up by primary key. No internal ordering is needed.", "world_line": null, "session_column": null, "confidence": "HIGH", "notes": "This is a dimension table of AI job postings. Each row represents a distinct job listing with attributes like title, salary, location, skills, and company. The job_id serves as the primary identifier. While posting_date and application_deadline exist as temporal attributes, they describe when the job was posted/expires rather than creating a timeline — this is reference data, not a time-series or event log." } ] } ```