这是本系列的最后一篇,主要是select_related() 和 prefetch_related() 的最佳实践。
第一篇在这里 讲例子和select_related()
第二篇在这里 讲prefetch_related()
>>> hb = Province.objects.get(name__iexact=u"湖北省") >>> people = [] >>> for city in hb.city_set.all(): ... people.extend(city.birth.all()) ...显然这不是一个明智的选择,因为这样做会导致1+(湖北省城市数)次SQL查询。反正是个反例,导致的查询和获得掉结果就不列出来了。
>>> hb = Province.objects.prefetch_related("city_set__birth").objects.get(name__iexact=u"湖北省") >>> people = [] >>> for city in hb.city_set.all(): ... people.extend(city.birth.all()) ...因为是一个深度为2的prefetch,所以会导致3次SQL查询:
SELECT `QSOptimize_province`.`id`, `QSOptimize_province`.`name` FROM `QSOptimize_province` WHERE `QSOptimize_province`.`name` LIKE '湖北省' ; SELECT `QSOptimize_city`.`id`, `QSOptimize_city`.`name`, `QSOptimize_city`.`province_id` FROM `QSOptimize_city` WHERE `QSOptimize_city`.`province_id` IN (1); SELECT `QSOptimize_person`.`id`, `QSOptimize_person`.`firstname`, `QSOptimize_person`.`lastname`, `QSOptimize_person`.`hometown_id`, `QSOptimize_person`.`living_id` FROM `QSOptimize_person` WHERE `QSOptimize_person`.`hometown_id` IN (1, 3);
>>> people = list(Person.objects.select_related("hometown__province").filter(hometown__province__name__iexact=u"湖北省"))
SELECT `QSOptimize_person`.`id`, `QSOptimize_person`.`firstname`, `QSOptimize_person`.`lastname`, `QSOptimize_person`.`hometown_id`, `QSOptimize_person`.`living_id`, `QSOptimize_city`.`id`, `QSOptimize_city`.`name`, `QSOptimize_city`.`province_id`, `QSOptimize_province`.`id`, `QSOptimize_province`.`name` FROM `QSOptimize_person` INNER JOIN `QSOptimize_city` ON (`QSOptimize_person`.`hometown_id` = `QSOptimize_city`.`id`) INNER JOIN `QSOptimize_province` ON (`QSOptimize_city`.`province_id` = `QSOptimize_province`.`id`) WHERE `QSOptimize_province`.`name` LIKE '湖北省';
+----+-----------+----------+-------------+-----------+----+--------+-------------+----+--------+ | id | firstname | lastname | hometown_id | living_id | id | name | province_id | id | name | +----+-----------+----------+-------------+-----------+----+--------+-------------+----+--------+ | 1 | 张 | 三 | 3 | 1 | 3 | 十堰市 | 1 | 1 | 湖北省 | | 2 | 李 | 四 | 1 | 3 | 1 | 武汉市 | 1 | 1 | 湖北省 | | 3 | 王 | 麻子 | 3 | 2 | 3 | 十堰市 | 1 | 1 | 湖北省 | +----+-----------+----------+-------------+-----------+----+--------+-------------+----+--------+ 3 rows in set (0.00 sec)完全没问题。不仅SQL查询的数量减少了,python程序上也精简了。
class Order(models.Model): customer = models.ForeignKey(Person) orderinfo = models.CharField(max_length=50) time = models.DateTimeField(auto_now_add = True) def __unicode__(self): return self.orderinfo如果我们拿到了一个订单的id 我们要知道这个订单的客户去过的省份。因为有ManyToManyField显然必须要用prefetch_related()。如果只用prefetch_related()会怎样呢?
>>> plist = Order.objects.prefetch_related('customer__visitation__province').get(id=1) >>> for city in plist.customer.visitation.all(): ... print city.province.name ...显然,关系到了4个表:Order、Person、City、Province,根据prefetch_related()的特性就得有4次SQL查询
SELECT `QSOptimize_order`.`id`, `QSOptimize_order`.`customer_id`, `QSOptimize_order`.`orderinfo`, `QSOptimize_order`.`time` FROM `QSOptimize_order` WHERE `QSOptimize_order`.`id` = 1 ; SELECT `QSOptimize_person`.`id`, `QSOptimize_person`.`firstname`, `QSOptimize_person`.`lastname`, `QSOptimize_person`.`hometown_id`, `QSOptimize_person`.`living_id` FROM `QSOptimize_person` WHERE `QSOptimize_person`.`id` IN (1); SELECT (`QSOptimize_person_visitation`.`person_id`) AS `_prefetch_related_val`, `QSOptimize_city`.`id`, `QSOptimize_city`.`name`, `QSOptimize_city`.`province_id` FROM `QSOptimize_city` INNER JOIN `QSOptimize_person_visitation` ON (`QSOptimize_city`.`id` = `QSOptimize_person_visitation`.`city_id`) WHERE `QSOptimize_person_visitation`.`person_id` IN (1); SELECT `QSOptimize_province`.`id`, `QSOptimize_province`.`name` FROM `QSOptimize_province` WHERE `QSOptimize_province`.`id` IN (1, 2);
+----+-------------+---------------+---------------------+ | id | customer_id | orderinfo | time | +----+-------------+---------------+---------------------+ | 1 | 1 | Info of Order | 2014-08-10 17:05:48 | +----+-------------+---------------+---------------------+ 1 row in set (0.00 sec) +----+-----------+----------+-------------+-----------+ | id | firstname | lastname | hometown_id | living_id | +----+-----------+----------+-------------+-----------+ | 1 | 张 | 三 | 3 | 1 | +----+-----------+----------+-------------+-----------+ 1 row in set (0.00 sec) +-----------------------+----+--------+-------------+ | _prefetch_related_val | id | name | province_id | +-----------------------+----+--------+-------------+ | 1 | 1 | 武汉市 | 1 | | 1 | 2 | 广州市 | 2 | | 1 | 3 | 十堰市 | 1 | +-----------------------+----+--------+-------------+ 3 rows in set (0.00 sec) +----+--------+ | id | name | +----+--------+ | 1 | 湖北省 | | 2 | 广东省 | +----+--------+ 2 rows in set (0.00 sec)
>>> plist = Order.objects.select_related('customer').prefetch_related('customer__visitation__province').get(id=1) >>> for city in plist.customer.visitation.all(): ... print city.province.name ...这样只会有3次SQL查询,Django会先做select_related,之后prefetch_related的时候会利用之前缓存的数据,从而避免了1次额外的SQL查询:
SELECT `QSOptimize_order`.`id`, `QSOptimize_order`.`customer_id`, `QSOptimize_order`.`orderinfo`, `QSOptimize_order`.`time`, `QSOptimize_person`.`id`, `QSOptimize_person`.`firstname`, `QSOptimize_person`.`lastname`, `QSOptimize_person`.`hometown_id`, `QSOptimize_person`.`living_id` FROM `QSOptimize_order` INNER JOIN `QSOptimize_person` ON (`QSOptimize_order`.`customer_id` = `QSOptimize_person`.`id`) WHERE `QSOptimize_order`.`id` = 1 ; SELECT (`QSOptimize_person_visitation`.`person_id`) AS `_prefetch_related_val`, `QSOptimize_city`.`id`, `QSOptimize_city`.`name`, `QSOptimize_city`.`province_id` FROM `QSOptimize_city` INNER JOIN `QSOptimize_person_visitation` ON (`QSOptimize_city`.`id` = `QSOptimize_person_visitation`.`city_id`) WHERE `QSOptimize_person_visitation`.`person_id` IN (1); SELECT `QSOptimize_province`.`id`, `QSOptimize_province`.`name` FROM `QSOptimize_province` WHERE `QSOptimize_province`.`id` IN (1, 2);
+----+-------------+---------------+---------------------+----+-----------+----------+-------------+-----------+ | id | customer_id | orderinfo | time | id | firstname | lastname | hometown_id | living_id | +----+-------------+---------------+---------------------+----+-----------+----------+-------------+-----------+ | 1 | 1 | Info of Order | 2014-08-10 17:05:48 | 1 | 张 | 三 | 3 | 1 | +----+-------------+---------------+---------------------+----+-----------+----------+-------------+-----------+ 1 row in set (0.00 sec) +-----------------------+----+--------+-------------+ | _prefetch_related_val | id | name | province_id | +-----------------------+----+--------+-------------+ | 1 | 1 | 武汉市 | 1 | | 1 | 2 | 广州市 | 2 | | 1 | 3 | 十堰市 | 1 | +-----------------------+----+--------+-------------+ 3 rows in set (0.00 sec) +----+--------+ | id | name | +----+--------+ | 1 | 湖北省 | | 2 | 广东省 | +----+--------+ 2 rows in set (0.00 sec)
值得注意的是,可以在调用prefetch_related之前调用select_related,并且Django会按照你想的去做:先select_related,然后利用缓存到的数据prefetch_related。然而一旦prefetch_related已经调用,select_related将不起作用。
实例详解Django的 select_related 和 prefetch_related 函数对 QuerySet 查询的优化(三),布布扣,bubuko.com
实例详解Django的 select_related 和 prefetch_related 函数对 QuerySet 查询的优化(三)
原文:http://blog.csdn.net/cugbabybear/article/details/38460877