{
  "schema_version": "1.0",
  "experiment": "5-10",
  "run_id": "20260729T205753Z-5_10-postgresql",
  "started_at_utc": "2026-07-29T20:57:53.576348+00:00",
  "completed_at_utc": "2026-07-29T21:00:59.416195+00:00",
  "provider": "ark",
  "endpoint": "https://ark.cn-beijing.volces.com/api/v3",
  "model": "doubao-seed-1-6-250615",
  "postgresql": {
    "version": "PostgreSQL 14.13 (Homebrew) on aarch64-apple-darwin23.6.0, compiled by Apple clang version 16.0.0 (clang-1600.0.26.4), 64-bit",
    "database": "postgres",
    "schema": "exp5_10_20260729t205753z510postgresql",
    "employees": 40,
    "salary_rows": 1184
  },
  "source": {
    "manuscript": "book/chapter5.md#实验-5-10",
    "campaign_sha256": "86afa359e0fca72397df53ca52149e11b2c5b0522001f583e56193e1d7eecbd2",
    "seed_sha256": "833c1a09349802dfad70c84b7d568d1e06ec3d73bdef588c796b2d704a73730d"
  },
  "records": [
    {
      "id": 1,
      "question": "平均每个员工在职多久？",
      "sql": "SELECT AVG(COALESCE(leave_date, CURRENT_DATE) - hire_date) AS average_tenure_days FROM employees",
      "rows": [
        [
          886.2
        ]
      ],
      "row_count": 1,
      "query_latency_s": 0.0036,
      "expected": [
        [
          886.2
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    },
    {
      "id": 2,
      "question": "每个部门有多少在职员工？",
      "sql": "SELECT department, COUNT(*) AS active_count FROM employees WHERE leave_date IS NULL GROUP BY department",
      "rows": [
        [
          "人力资源部",
          4
        ],
        [
          "市场部",
          9
        ],
        [
          "研发部",
          5
        ],
        [
          "财务部",
          6
        ],
        [
          "销售部",
          10
        ]
      ],
      "row_count": 5,
      "query_latency_s": 0.0023,
      "expected": [
        [
          "研发部",
          5
        ],
        [
          "销售部",
          10
        ],
        [
          "人力资源部",
          4
        ],
        [
          "市场部",
          9
        ],
        [
          "财务部",
          6
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    },
    {
      "id": 3,
      "question": "哪个部门员工平均级别最高？",
      "sql": "SELECT department\nFROM employees\nGROUP BY department\nORDER BY AVG(level) DESC\nLIMIT 1",
      "rows": [
        [
          "销售部"
        ]
      ],
      "row_count": 1,
      "query_latency_s": 0.0023,
      "expected": [
        [
          "销售部"
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    },
    {
      "id": 4,
      "question": "每个部门今年和去年各新入职多少人？",
      "sql": "SELECT department,\n       COUNT(*) FILTER (WHERE EXTRACT(YEAR FROM hire_date) = EXTRACT(YEAR FROM CURRENT_DATE)) AS this_year_count,\n       COUNT(*) FILTER (WHERE EXTRACT(YEAR FROM hire_date) = EXTRACT(YEAR FROM CURRENT_DATE) - 1) AS last_year_count\nFROM employees\nGROUP BY department\nHAVING this_year_count > 0 OR last_year_count > 0",
      "rows": [],
      "row_count": 0,
      "query_latency_s": 0.0047,
      "expected": [
        [
          "研发部",
          1,
          2
        ],
        [
          "销售部",
          2,
          1
        ],
        [
          "人力资源部",
          2,
          0
        ],
        [
          "市场部",
          0,
          4
        ],
        [
          "财务部",
          0,
          1
        ]
      ],
      "passed": false,
      "comparison": "UndefinedColumn: column \"this_year_count\" does not exist\nLINE 6: HAVING this_year_count > 0 OR last_year_count > 0\n               ^\n"
    },
    {
      "id": 5,
      "question": "前年3月到去年5月，A部门平均工资是多少？",
      "sql": "SELECT AVG(s.salary)\nFROM employees e\nJOIN salaries s ON e.emp_id = s.emp_id\nWHERE e.department = '研发部'\n  AND s.pay_date BETWEEN make_date(EXTRACT(YEAR FROM CURRENT_DATE)::INTEGER - 2, 3, 1)\n                      AND make_date(EXTRACT(YEAR FROM CURRENT_DATE)::INTEGER - 1, 5, 31)",
      "rows": [
        [
          27695.833333333332
        ]
      ],
      "row_count": 1,
      "query_latency_s": 0.0038,
      "expected": [
        [
          27695.83
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    },
    {
      "id": 6,
      "question": "去年A部门和B部门平均工资哪个高？",
      "sql": "SELECT e.department, AVG(s.salary) AS average_salary\nFROM employees e\nINNER JOIN salaries s ON e.emp_id = s.emp_id\nWHERE e.department IN ('研发部', '销售部')\n  AND s.pay_date >= date_trunc('year', CURRENT_DATE) - INTERVAL '1 year'\n  AND s.pay_date < date_trunc('year', CURRENT_DATE)\nGROUP BY e.department",
      "rows": [
        [
          "研发部",
          28569.444444444445
        ],
        [
          "销售部",
          29481.55339805825
        ]
      ],
      "row_count": 2,
      "query_latency_s": 0.0054,
      "expected": [
        [
          "研发部",
          28569.44
        ],
        [
          "销售部",
          29481.55
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    },
    {
      "id": 7,
      "question": "今年每个级别的员工平均工资是多少？",
      "sql": "SELECT e.level, AVG(s.salary) AS average_salary\nFROM employees e\nJOIN salaries s ON e.emp_id = s.emp_id\nWHERE EXTRACT(YEAR FROM s.pay_date) = EXTRACT(YEAR FROM CURRENT_DATE)\nGROUP BY e.level",
      "rows": [
        [
          3,
          23456.428571428572
        ],
        [
          4,
          26248.823529411766
        ],
        [
          5,
          34534.75
        ],
        [
          6,
          28461.363636363636
        ],
        [
          7,
          29935.0
        ],
        [
          8,
          32242.69230769231
        ],
        [
          9,
          34559.90566037736
        ]
      ],
      "row_count": 7,
      "query_latency_s": 0.0016,
      "expected": [
        [
          3,
          23456.43
        ],
        [
          8,
          32242.69
        ],
        [
          6,
          28461.36
        ],
        [
          4,
          26248.82
        ],
        [
          9,
          34559.91
        ],
        [
          5,
          34534.75
        ],
        [
          7,
          29935
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    },
    {
      "id": 8,
      "question": "入职一年内、一到两年、两到三年的员工，最近一个月平均工资是多少？",
      "sql": "WITH latest_salaries AS (\n    SELECT DISTINCT ON (emp_id) emp_id, salary\n    FROM salaries\n    ORDER BY emp_id, pay_date DESC\n)\nSELECT \n    CASE \n        WHEN (CURRENT_DATE - e.hire_date)::INTEGER < 365 THEN '入职一年内'\n        WHEN (CURRENT_DATE - e.hire_date)::INTEGER BETWEEN 365 AND 729 THEN '一到两年'\n        WHEN (CURRENT_DATE - e.hire_date)::INTEGER BETWEEN 730 AND 1094 THEN '两到三年'\n    END AS bucket,\n    AVG(ls.salary) AS average_latest_salary\nFROM employees e\nJOIN latest_salaries ls ON e.emp_id = ls.emp_id\nWHERE e.leave_date IS NULL\n    AND (CURRENT_DATE - e.hire_date)::INTEGER <= 1094\nGROUP BY bucket",
      "rows": [
        [
          "一到两年",
          27683.125
        ],
        [
          "两到三年",
          31138.75
        ],
        [
          "入职一年内",
          24053.75
        ]
      ],
      "row_count": 3,
      "query_latency_s": 0.0018,
      "expected": [
        [
          "入职一年内",
          24053.75
        ],
        [
          "一到两年",
          27683.12
        ],
        [
          "两到三年",
          31138.75
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    },
    {
      "id": 9,
      "question": "去年到今年涨薪幅度最大的10位员工是谁？",
      "sql": "WITH employee_salary_avg AS (\n    SELECT \n        emp_id,\n        AVG(salary) FILTER (WHERE EXTRACT(YEAR FROM pay_date) = EXTRACT(YEAR FROM CURRENT_DATE) - 1) AS avg_prev_year,\n        AVG(salary) FILTER (WHERE EXTRACT(YEAR FROM pay_date) = EXTRACT(YEAR FROM CURRENT_DATE)) AS avg_curr_year\n    FROM salaries\n    GROUP BY emp_id\n    HAVING AVG(salary) FILTER (WHERE EXTRACT(YEAR FROM pay_date) = EXTRACT(YEAR FROM CURRENT_DATE) - 1) IS NOT NULL\n       AND AVG(salary) FILTER (WHERE EXTRACT(YEAR FROM pay_date) = EXTRACT(YEAR FROM CURRENT_DATE)) IS NOT NULL\n)\nSELECT e.name, (esa.avg_curr_year - esa.avg_prev_year) AS raise_amount\nFROM employee_salary_avg esa\nJOIN employees e ON esa.emp_id = e.emp_id\nORDER BY raise_amount DESC\nLIMIT 10",
      "rows": [
        [
          "韩平",
          12000.0
        ],
        [
          "韩伟",
          2200.0
        ],
        [
          "吕芳",
          2155.0
        ],
        [
          "金丽",
          2110.0
        ],
        [
          "许华",
          2065.0
        ],
        [
          "陶松",
          1975.0
        ],
        [
          "周雪",
          1930.0
        ],
        [
          "吴敏",
          1885.0
        ],
        [
          "张霞",
          1840.0
        ],
        [
          "赵平",
          1795.0
        ]
      ],
      "row_count": 10,
      "query_latency_s": 0.0016,
      "expected": [
        [
          "韩平",
          12000
        ],
        [
          "韩伟",
          2200
        ],
        [
          "吕芳",
          2155
        ],
        [
          "金丽",
          2110
        ],
        [
          "许华",
          2065
        ],
        [
          "陶松",
          1975
        ],
        [
          "周雪",
          1930
        ],
        [
          "吴敏",
          1885
        ],
        [
          "张霞",
          1840
        ],
        [
          "赵平",
          1795
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    },
    {
      "id": 10,
      "question": "有没有拖欠工资的情况（某个月还在职却没有发薪）？",
      "sql": "WITH employed_months AS (\n    SELECT \n        e.emp_id,\n        generate_series(\n            date_trunc('month', e.hire_date),\n            date_trunc('month', COALESCE(e.leave_date, CURRENT_DATE)),\n            interval '1 month'\n        ) AS month\n    FROM employees e\n)\nSELECT \n    em.emp_id,\n    to_char(em.month, 'YYYY-MM') AS month\nFROM employed_months em\nLEFT JOIN salaries s \n    ON em.emp_id = s.emp_id \n    AND em.month = date_trunc('month', s.pay_date)\nWHERE s.emp_id IS NULL",
      "rows": [
        [
          17,
          "2026-01"
        ]
      ],
      "row_count": 1,
      "query_latency_s": 0.0156,
      "expected": [
        [
          17,
          "2026-01"
        ]
      ],
      "passed": true,
      "comparison": "independent Python reference matched"
    }
  ],
  "browser": {
    "browser": "Chromium",
    "version": "139.0.7258.5",
    "html": "results.html",
    "screenshot": "results.png"
  },
  "usage": {
    "calls": 10,
    "prompt_tokens": 3154,
    "completion_tokens": 8642,
    "total_tokens": 11796,
    "model_latency_s": 184.439,
    "db_latency_s": 0.0427
  },
  "artifacts": {
    "employees.json": {
      "path": "employees.json",
      "sha256": "7e5e237da09edb3db029e367a52569267241673a99e19d2ffddbb85a45cb59bd"
    },
    "salaries.json": {
      "path": "salaries.json",
      "sha256": "70a9dcd335d5c3e277eac92a4ae351f0f33c56ef9b2a526047cf60c98ed04228"
    },
    "schema.sql": {
      "path": "schema.sql",
      "sha256": "76a7d9f85d8bf3998729c40fa448e61e49ec24d47acba2f04580e5d2aeb27596"
    },
    "receipts.json": {
      "path": "receipts.json",
      "sha256": "dd1009c0972f1b4a1a4509b5101d8b60f5de2058d6f6da60fdc0017e4c04e981"
    },
    "queries_and_results.json": {
      "path": "queries_and_results.json",
      "sha256": "4016b2cc9ef358262e5102604e05c2b6be187d53a74bd6b11a18dc386aea0465"
    },
    "results.html": {
      "path": "results.html",
      "sha256": "6ca358d98be1d2dd8de38d63e94c5793bb491a3a28f007f8cbff251f79d41415"
    },
    "results.png": {
      "path": "results.png",
      "sha256": "e7305970e395fb497a3d9eaf136e91cb89fe6adedbe4db65894e64234eb8d38d"
    }
  },
  "acceptance_gates": {
    "real_postgresql_server": true,
    "exact_two_table_schema_created": true,
    "all_10_natural_language_questions_attempted": true,
    "all_10_sql_artifacts_are_read_only": true,
    "database_not_llm_received_rows": true,
    "database_executed_every_artifact": true,
    "all_10_answers_match_independent_reference": false,
    "result_tables_rendered_directly_in_real_browser": true,
    "raw_model_receipts_complete": true,
    "raw_database_rows_and_hashes_retained": true
  },
  "official_complete": false
}