snowflake-sql
Snowflake-specific SQL patterns: QUALIFY for window filtering, LATERAL FLATTEN for arrays, semi-structured VARIANT data, ILIKE for case-insensitive matching, date functions, and time travel.
适合你,如果经常用 Snowflake 处理 JSON 数组或时间旅行查询
/ 通过 npx 安装 校验哈希
npx oh-my-skill add signalpilot-labs/signalpilot/snowflake-sql/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- signalpilot-labs/signalpilot/snowflake-sql/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify signalpilot-labs/signalpilot/snowflake-sql安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用
商店整理自技能原文 · 版本 436a4c4 · 表述以原文为准它做什么
当需要编写 Snowflake 特有的 SQL 查询时,Claude 会使用 QUALIFY、LATERAL FLATTEN、ILIKE、日期函数、时间旅行等 Snowflake 专属语法,并避免常见反模式。
什么时候触发
当用户询问或要求编写 Snowflake SQL 查询(如窗口过滤、半结构化数据处理、时间旅行等)时触发。
装好后可以这样说
Claude 会生成 QUALIFY 子句,无需子查询。
技能原文 SKILL.md
Snowflake SQL Skill
1. Window Function Filtering - Use QUALIFY
Instead of wrapping in a subquery, use QUALIFY:
-- Find the latest record per customer SELECT customer_id, order_date, amount FROM orders QUALIFY ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY order_date DESC) = 1; -- Top 5 products by sales SELECT product_id, total_sales FROM sales_summary QUALIFY DENSE_RANK() OVER (ORDER BY total_sales DESC) <= 5;
2. Case-Insensitive Matching - Use ILIKE
-- Case-insensitive LIKE WHERE product_name ILIKE '%widget%' -- Case-insensitive equality WHERE UPPER(status) = 'ACTIVE' -- or WHERE status ILIKE 'active'
3. Arrays and Semi-Structured Data - LATERAL FLATTEN
-- Explode an ARRAY column SELECT t.id, f.value AS item FROM table t, LATERAL FLATTEN(input => t.array_col) f; -- Access VARIANT fields SELECT col:field_name::STRING AS field_value FROM table; -- Parse JSON string SELECT PARSE_JSON(json_col):key::STRING AS val FROM table;
4. Date Functions
-- Add/subtract time
DATEADD(day, 7, order_date) -- 7 days from order_date
DATEADD(month, -1, current_date()) -- 1 month ago
-- Difference between dates
DATEDIFF(day, start_date, end_date) -- days between dates
DATEDIFF(month, start_date, end_date)
-- Truncate to period
DATE_TRUNC('month', event_ts)
DATE_TRUNC('year', event_ts)
-- Current timestamp
CURRENT_TIMESTAMP()
CURRENT_DATE()
5. String Functions
SPLIT_PART(col, '/', 1) -- split by delimiter, get Nth part REGEXP_SUBSTR(col, '[0-9]+') -- first match of regex TRIM(col) -- remove leading/trailing whitespace LTRIM(col, '0') -- remove leading zeros UPPER(col) / LOWER(col) CONCAT(col1, '-', col2) -- or col1 || '-' || col2
6. Null-Safe Equality
-- NULL-safe: TRUE when both are NULL or both equal col1 IS NOT DISTINCT FROM col2 -- COALESCE for default values COALESCE(col, 'unknown')
7. Time Travel (querying historical data)
-- Query table as it was 1 hour ago SELECT * FROM my_table AT (OFFSET => -3600); -- Query at a specific timestamp SELECT * FROM my_table AT (TIMESTAMP => '2024-01-01'::TIMESTAMP);
8. Common Anti-Patterns to Avoid
- Do NOT use
= NULL- useIS NULL - Do NOT use
<>for NULL comparison - useIS NOT NULL - Prefer
QUALIFYover subquery wrapping for window filters - When accessing VARIANT fields, always cast:
col:field::STRING
9. Benchmark Patterns
- Numeric precision: Snowflake returns DECIMAL/NUMBER with configurable precision. Do NOT cast to FLOAT unless needed - precision loss fails exact-match evaluation.
- IDENTIFIER case: Snowflake upper-cases identifiers by default. Use double-quotes
"lower_case_col"when column names are lowercase in source. Always check withdescribe_table. - LISTAGG: Use
LISTAGG(col, ',') WITHIN GROUP (ORDER BY col)for string aggregation (not GROUP_CONCAT). - TRY_CAST / TRY_TO_NUMBER: Use for safe type conversion that returns NULL instead of error.
- OBJECT_KEYS / ARRAY_SIZE: Useful for introspecting semi-structured data before querying.
按 Apache-2.0 许可原样转载,未经改动 · 在 GitHub 查看 →
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