# 问题分析
1. 慢查询分析：发现商品列表查询SQL执行时间超过1秒
2. 执行计划分析：全表扫描，没有使用索引
3. SQL语句：
SELECT * FROM fgedudb.fgedu_products WHERE category_id = 1 AND price > 100 ORDER BY sales DESC LIMIT 20;

# 优化措施
1. 索引优化：
CREATE INDEX idx_category_price_sales ON fgedudb.fgedu_products(category_id, price, sales);

2. SQL优化：
SELECT id, name, price, sales FROM fgedudb.fgedu_products WHERE category_id = 1 AND price > 100 ORDER BY sales DESC LIMIT 20;

3. 执行计划分析：
+————————-+———+———–+—————————————–+———————————————-+
| id | estRows | task | access object | operator info |
+————————-+———+———–+—————————————–+———————————————-+
| TopN_7 | 20.00 | root | | offset:0, count:20, sort:fgedu_products.sales DESC |
| └─IndexRangeScan_6 | 10000.00 | cop[tikv] | table:fgedu_products, index:idx_category_price_sales | range:[1,100,+inf], keep order:false |
+————————-+———+———–+—————————————–+———————————————-+

# 优化效果
– 查询响应时间：从1秒降低到100ms以内
– 系统QPS：从5000提升到10000
– 用户体验：明显改善，商品列表加载速度大幅提升

# 问题分析
1. 慢查询分析：发现交易历史查询SQL执行时间超过2秒
2. 执行计划分析：使用了全表扫描和临时表
3. SQL语句：
SELECT * FROM fgedudb.fgedu_transactions WHERE user_id = 12345 AND transaction_date BETWEEN ‘2024-01-01’ AND ‘2024-01-31’ ORDER BY transaction_date DESC;

# 优化措施
1. 索引优化：
CREATE INDEX idx_user_date ON fgedudb.fgedu_transactions(user_id, transaction_date);

2. SQL优化：
SELECT transaction_id, transaction_date, amount, type FROM fgedudb.fgedu_transactions WHERE user_id = 12345 AND transaction_date BETWEEN ‘2024-01-01’ AND ‘2024-01-31’ ORDER BY transaction_date DESC;

3. 分区表：
ALTER TABLE fgedudb.fgedu_transactions PARTITION BY RANGE(YEAR(transaction_date)) (
PARTITION p2023 VALUES LESS THAN (2024),
PARTITION p2024 VALUES LESS THAN (2025),
PARTITION p2025 VALUES LESS THAN (2026)
);

# 优化效果
– 查询响应时间：从2秒降低到200ms以内
– 系统QPS：从2000提升到5000
– 业务处理效率：显著提高，客户满意度提升

# 问题分析
1. 慢查询分析：发现生产报表SQL执行时间超过5分钟
2. 执行计划分析：使用了多个表的复杂JOIN操作
3. SQL语句：
SELECT p.product_name, SUM(o.quantity) as total_quantity, SUM(o.amount) as total_amount FROM fgedudb.fgedu_orders o JOIN fgedudb.fgedu_products p ON o.product_id = p.product_id WHERE o.order_date BETWEEN ‘2024-01-01’ AND ‘2024-01-31’ GROUP BY p.product_name ORDER BY total_amount DESC;

# 优化措施
1. 索引优化：
CREATE INDEX idx_order_product_date ON fgedudb.fgedu_orders(product_id, order_date);
CREATE INDEX idx_product_name ON fgedudb.fgedu_products(product_name);

2. SQL优化：
SELECT p.product_name, SUM(o.quantity) as total_quantity, SUM(o.amount) as total_amount FROM fgedudb.fgedu_orders o JOIN fgedudb.fgedu_products p ON o.product_id = p.product_id WHERE o.order_date BETWEEN ‘2024-01-01’ AND ‘2024-01-31’ GROUP BY p.product_id, p.product_name ORDER BY total_amount DESC;

3. 物化视图：
CREATE MATERIALIZED VIEW fgedu_order_summary AS SELECT product_id, SUM(quantity) as total_quantity, SUM(amount) as total_amount, DATE(order_date) as order_date FROM fgedudb.fgedu_orders GROUP BY product_id, DATE(order_date);

# 优化效果
– 查询响应时间：从5分钟降低到30秒以内
– 报表生成效率：显著提高，决策速度加快
– 系统负载：明显降低