```json { "table_name": "search_engine_benchmark", "primary_key": "id", "candidates": [ { "rank": 0, "partition_key": "id", "partition_key_label": "primary_identifier", "partition_key_reasoning": "RPUV=1.00, uniqueness=1.000, serves as the unique identifier for each benchmark run. Each row represents a distinct search engine benchmark result (whoosh, tantivy, lucene).", "clustering_key": null, "clustering_key_label": null, "clustering_key_reasoning": "Dimension tables typically do not require clustering. The table is small (3 rows) and represents distinct benchmark configurations rather than ordered sequences.", "world_line": null, "session_column": null, "confidence": "HIGH", "notes": "This is a dimension table cataloging search engine benchmark results. The id column is the natural primary key. The table is extremely small (3 rows) representing three different search engines (whoosh, tantivy, lucene) tested against the same probe set version (v1). All other columns are either constant (probe_set_version, queries_run, corpus_docs, created_at) or measurement metrics (precision_at_k, recall_at_k, build_ms, query_ms, index_bytes). No alternative partitioning perspectives are viable given the table's purpose as a reference/lookup table for benchmark results." } ] } ```