sql-optimization
Applies SQL optimization patterns, window functions, and Snowflake-specific tuning; use when writing complex queries, optimizing slow queries, designing indexes, or reviewing query performance.
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- 최근 소스 활동
- 2026년 10월 16일 19:08
- 감지된 SKILL.md 언어
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- 19
- 포크
- 4
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- sql-optimization
- description
- Applies SQL optimization patterns, window functions, and Snowflake-specific tuning; use when writing complex queries, optimizing slow queries, designing indexes, or reviewing query performance.
# Skill: SQL Optimization
## When to load
When writing complex queries, optimizing slow queries, designing indexes, or reviewing query performance.
## Core Patterns
```sql
-- ✅ Column projection — never SELECT *
SELECT user_id, created_at, total_amount FROM orders WHERE created_at >= '2026-01-01';
-- ✅ Partition pruning — filter on partition column first
SELECT user_id, total_amount
FROM orders
WHERE order_date = '2026-01-15' -- partition filter first
AND status = 'completed';
-- ❌ Function on indexed column defeats index
WHERE DATE(created_at) = '2026-01-15'
-- ✅ Range comparison preserves index
WHERE created_at >= '2026-01-15' AND created_at < '2026-01-16'
```
## Window Functions (prefer over self-joins)
```sql
SELECT
user_id, order_date, amount,
SUM(amount) OVER (
PARTITION BY user_id ORDER BY order_date
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
) AS cumulative_amount,
ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY order_date DESC) AS recency_rank
FROM orders;
```
## Snowflake-Specific
```sql
-- Cluster keys on large tables (> 1 TB)
ALTER TABLE orders CLUSTER BY (order_date, status);
-- COPY INTO for bulk loads — never row-by-row INSERT
COPY INTO orders FROM @my_stage/orders/
FILE_FORMAT = (TYPE = PARQUET) MATCH_BY_COLUMN_NAME = CASE_INSENSITIVE;
```
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