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Analytical SQL engine for querying CSV, Parquet, and JSON files directly. No database setup required.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
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| name | duckdb-sql |
| description | Analytical SQL engine for querying CSV, Parquet, and JSON files directly. No database setup required. |
| metadata | {"xiaodazi":{"dependency_level":"lightweight","os":["common"],"backend_type":"local","user_facing":true,"python_packages":["duckdb"]}} |
| capabilities | ["data_analysis","sql_query"] |
用 SQL 直接查询 CSV、Parquet、JSON 文件，无需导入数据库。适合大数据集分析。
| 工具 | 擅长 | 局限 |
|---|---|---|
| excel-analyzer | 小数据集、图表、格式化输出 | 大数据集慢 |
| duckdb-sql | 大数据集、复杂 SQL、多文件 JOIN | 不做格式化输出 |
import duckdb
con = duckdb.connect()
# 直接查询 CSV
result = con.sql("SELECT * FROM 'data.csv' LIMIT 10").fetchdf()
# 聚合分析
result = con.sql("""
SELECT category, COUNT(*) as count, AVG(price) as avg_price
FROM 'sales.csv'
GROUP BY category
ORDER BY count DESC
""").fetchdf()
# 多文件 JOIN
result = con.sql("""
SELECT o.order_id, c.name, o.total
FROM 'orders.csv' o
JOIN 'customers.csv' c ON o.customer_id = c.id
WHERE o.total > 1000
""").fetchdf()
# 查询 Parquet
result = con.sql("SELECT * FROM 'data.parquet' WHERE year = 2026").fetchdf()
# 通配符查询多文件
result = con.sql("SELECT * FROM 'logs/*.csv'").fetchdf()
# 安装
pip install duckdb
# 交互式
python3 -c "import duckdb; print(duckdb.sql(\"SELECT count(*) FROM 'data.csv'\").fetchone())"
-- 数据概览
SUMMARIZE SELECT * FROM 'data.csv';
-- 去重计数
SELECT COUNT(DISTINCT user_id) FROM 'events.csv';
-- 窗口函数：排名
SELECT *, RANK() OVER (PARTITION BY department ORDER BY salary DESC) as rank
FROM 'employees.csv';
-- 导出结果
COPY (SELECT * FROM 'data.csv' WHERE status = 'active') TO 'output.csv';