结合业务特性巧用临时表



拿到某开发sql如下SELECTp.products_idFROMproductsASpJOINproducts_to_categoriesASpcUSING(products_id)JOINcategoriesAScUSING(categories_id)JOINproducts_r

拿到某开发sql如下

SELECT p.products_id FROM products AS p JOIN products_to_categories AS pc USING(products_id) JOIN categories AS c USING(categories_id) JOIN products_realtime_quantity AS prq ON prq.sku_or_poa = p.products_model WHERE products_status =1 AND categories_status =1 AND prq.msg != 'Temporary out stock.' ORDER BY p.products_date_added DESC LIMIT 10

一般看到这种sql,在where中只有status类似的字段(可选择性非常低,数据两极分化非常明显)而且需要order by的语句,我们就应该想到使用force index(order_by_column)来进行优化.

explian

+----+-------------+-------+--------+------------------------------+-------------------+---------+--------------------------------+--------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+------------------------------+-------------------+---------+--------------------------------+--------+----------------------------------------------+ | 1 | SIMPLE | pc | index | PRIMARY,categories_id | PRIMARY | 8 | NULL | 1009510 | Using index; Using temporary; Using filesort | | 1 | SIMPLE | p | eq_ref | PRIMARY,products_model | PRIMARY | 4 | banggood_work.pc.products_id | 1 | Using where | | 1 | SIMPLE | c | eq_ref | PRIMARY | PRIMARY | 4 | banggood_work.pc.categories_id | 1 | Using where | | 1 | SIMPLE | prq | ref | ix_prg_sku_or_poa,ix_prq_msg | ix_prg_sku_or_poa | 152 | banggood_work.p.products_model | 1 | Using where | +----+-------------+-------+--------+------------------------------+-------------------+---------+--------------------------------+--------+----------------------------------------------+

发现mysql优化器选择了pc表的主键,虽然使用了索引,但是进行了全索引扫描，效果还是不理想!

强制使用force index后,explain

EXPLAIN -> SELECT p.products_id FROM products AS p FORCE INDEX(products_date_added) -> JOIN products_to_categories AS pc USING(products_id) -> JOIN categories AS c USING(categories_id) -> JOIN products_realtime_quantity AS prq ON prq.sku_or_poa = p.products_model -> WHERE products_status =1 AND categories_status =1 AND prq.msg != 'Temporary out stock.' -> ORDER BY p.products_date_added DESC LIMIT 10 -> ; +----+-------------+-------+--------+------------------------------+---------------------+---------+--------------------------------+------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+------------------------------+---------------------+---------+--------------------------------+------+-------------+ | 1 | SIMPLE | p | index | NULL | products_date_added | 8 | NULL | 1 | Using where | | 1 | SIMPLE | prq | ref | ix_prg_sku_or_poa,ix_prq_msg | ix_prg_sku_or_poa | 152 | banggood_work.p.products_model | 1 | Using where | | 1 | SIMPLE | pc | ref | PRIMARY,categories_id | PRIMARY | 4 | banggood_work.p.products_id | 1009 | Using index | | 1 | SIMPLE | c | eq_ref | PRIMARY | PRIMARY | 4 | banggood_work.pc.categories_id | 1 | Using where | +----+-------------+-------+--------+------------------------------+---------------------+---------+--------------------------------+------+-------------+

发现索引已经变成productsw_date_added,而执行时间，前者是2s,后者是0.003s.

这是我们一贯的优化方法,但是我们可以根据sql语句的特性和业务特性,结合临时表进行一些淫邪的优化，虽然并不通用，但是可以开阔sql优化者的思维。

我们可以看到这条语句是需要根据产品添加时间拿取符合(products_status =1 AND categories_status =1 AND prq.msg != 'Temporary out stock.')条件的10个最新上架产品.而我们知道，最新上架的产品一般状态都是不可能马上下架,而且对应的类别id也是可用,而且库存也是充足的(要不然何必上架),这个特性站到了99.9%以上.所以，我们利用这个特性，，先从产品表中找出不带任何条件的200个产品,放到临时表,然后再用临时表结果集,和拿取条件进行匹配,取出最新的10条.

(200条是一个参考值，根据各自的逻辑特性来取)

sql如下

SELECT DISTINCT p.products_id FROM (SELECT products_id,products_model,products_status,products_date_added FROM products ORDER BY products_date_added DESC LIMIT 200 ) AS p JOIN products_to_categories AS pc USING(products_id) JOIN categories AS c USING(categories_id) JOIN products_realtime_quantity AS prq ON prq.sku_or_poa = p.products_model WHERE products_status =1 AND categories_status =1 AND prq.msg != 'Temporary out stock.' ORDER BY products_date_added DESC LIMIT 10;

explain后发现

| 1 | PRIMARY | | ALL | NULL | NULL | NULL | NULL | 200 | Using where; Using temporary; Using filesort | | 1 | PRIMARY | prq | ref | ix_prg_sku_or_poa,ix_prq_msg | ix_prg_sku_or_poa | 152 | p.products_model | 1 | Using where; Distinct | | 1 | PRIMARY | pc | ref | PRIMARY,categories_id | PRIMARY | 4 | p.products_id | 1009 | Using index; Distinct | | 1 | PRIMARY | c | eq_ref | PRIMARY | PRIMARY | 4 | banggood_work.pc.categories_id | 1 | Using where; Distinct | | 2 | DERIVED | products | index | NULL | products_date_added | 8 | NULL | 200 | |

我们可以看到，已经利用products表中的products_date_added字段排序取出200条,整个sql语句变成一个只有200行的临时表驱动查询了，性能相对于原来的语句,提高上百倍！

执行时间大约是0.02s(可能比force index略慢)。

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