我有一个选择查询，该查询一次从mysql 5.5数据库中选择了超过5万条记录，并且这个数量有望增长。该查询包含多个子查询，这些子查询要花120多秒才能执行。
最初，sale_items和stock中的某些表没有ID密钥，因此我添加了更多
SELECT
`p`.`id` AS `id`,
`p`.`Name` AS `Name`,
`p`.`Created` AS `Created`,
`p`.`Image` AS `Image`,
`s`.`company` AS `supplier`,
`s`.`ID` AS `supplier_id`,
`c`.`name` AS `category`,
IFNULL((SELECT
SUM(`stocks`.`Total_Quantity`)
FROM `stocks`
WHERE (`stocks`.`Product_ID` = `p`.`id`)), 0) AS `total_qty`,
IFNULL((SELECT
SUM(`sale_items`.`quantity`)
FROM `sale_items`
WHERE (`sale_items`.`product_id` = `p`.`id`)), 0) AS `total_sold`,
IFNULL((SELECT
SUM(`sale_items`.`quantity`)
FROM `sale_items`
WHERE ((`sale_items`.`product_id` = `p`.`id`) AND `sale_items`.`Sale_ID` IN (SELECT
`refunds`.`Sale_ID`
FROM `refunds`))), 0) AS `total_refund`
FROM ((`products` `p`
LEFT JOIN `cats` `c`
ON ((`c`.`ID` = `p`.`cat_id`)))
LEFT JOIN `suppliers` `s`
ON ((`s`.`ID` = `p`.`supplier_id`)))
这是解释结果
+----+--------------------+------------+----------------+------------------------+------------------------+---------+---------------------------------
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+--------------------+------------+----------------+------------------------+------------------------+---------+---------------------------------
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 20981 | |
| 2 | DERIVED | p | ALL | NULL | NULL | NULL | NULL | 20934 | |
| 2 | DERIVED | c | eq_ref | PRIMARY | PRIMARY | 4 | p.cat_id | 1 | |
| 2 | DERIVED | s | eq_ref | PRIMARY | PRIMARY | 4 | p.supplier_id | 1 | |
| 5 | DEPENDENT SUBQUERY | sale_items | ref | sales_items_product_id | sales_items_product_id | 5 | p.id | 33 | Using where |
| 6 | DEPENDENT SUBQUERY | refunds | index_subquery | IDX_refunds_sale_id | IDX_refunds_sale_id | 5 | func | 1 | Using index; Using where |
| 4 | DEPENDENT SUBQUERY | sale_items | ref | sales_items_product_id | sales_items_product_id | 5 | p.id | 33 | Using where |
| 3 | DEPENDENT SUBQUERY | stocks | ref | IDX_stocks_product_id | IDX_stocks_product_id | 5 | p.id | 1 | Using where |
+----+--------------------+------------+----------------+------------------------+------------------------+---------+---------------------------------
我希望查询最多花费不到3秒的时间，但是我似乎无法找出优化此查询的最佳方法
答案 0 :(得分：2)
查询对我来说很好。您选择所有数据并汇总其中一些数据。这需要时间。您的解释计划显示ID上有索引，这很好。乍一看，我们在这里似乎无能为力...
但是，您可以 做的是提供覆盖索引，即包含表中需要的所有列的索引，因此可以直接从索引中获取数据。
group = c(0,0,1,1,1,0,0,2,2,2,2,2,2,0,0,0,0,0,0)
data.frame(df, group)
这确实可以增强您的查询。
您可以尝试的关于查询本身的方法是将子查询移至create index idx1 on cats(id, name);
create index idx2 on suppliers(id, company);
create index idx3 on stocks(product_id, total_quantity);
create index idx4 on sale_items(product_id, quantity, sale_id);
子句。 MySQL的优化器不是很好，因此尽管它应该获得相同的执行计划，但很可能是因为它偏爱FROM子句。
FROM（如果SELECT
p.id,
p.name,
p.created,
p.image,
s.company as supplier,
s.id AS supplier_id,
c.name AS category,
COALESCE(st.total, 0) AS total_qty,
COALESCE(si.total, 0) AS total_sold,
COALESCE(si.refund, 0) AS total_refund
FROM products p
LEFT JOIN cats c ON c.id = p.cat_id
LEFT JOIN suppliers s ON s.id = p.supplier_id
LEFT JOIN
(
SELECT SUM(total_quantity) AS total
FROM stocks
GROUP BY product_id
) st ON st.product_id = p.id
LEFT JOIN
(
SELECT
SUM(quantity) AS total,
SUM(CASE WHEN sale_id IN (SELECT sale_id FROM refunds) THEN quantity END) as refund
FROM sale_items
GROUP BY product_id
) si ON si.product_id = p.id;
在sale_id中是唯一的，那么您甚至可以将其加入refunds。同样：这通常没有什么区别，但是在MySQL中它仍然可以。曾经因对待sale_items子句比IN子句差得多而臭名昭著。我不知道情况可能不再如此。您可以尝试-如果FROM是唯一的）。