转载的,做个笔记,
在数据库有外键的时候，使用 select_related() 和 prefetch_related() 可以很好的减少数据库请求的次数，从而提高性能。本文通过一个简单的例子详解这两个函数的作用。虽然QuerySet的文档中已经详细说明了，但本文试图从QuerySet触发的SQL语句来分析工作方式，从而进一步了解Django具体的运作方式。
实例背景
假定一个个人信息系统，需要记录系统中各个人的故乡、居住地、以及到过的城市。数据库设计如下：
models.py 内容:
from django.db import modelsclass Province(models.Model): name = models.CharField(max_length=10) def __unicode__(self): return self.nameclass City(models.Model): name = models.CharField(max_length=5) province = models.ForeignKey(Province) def __unicode__(self): return self.nameclass Person(models.Model): firstname = models.CharField(max_length=10) lastname = models.CharField(max_length=10) visitation = models.ManyToManyField(City, related\_name = "visitor") hometown = models.ForeignKey(City, related\_name = "birth") living = models.ForeignKey(City, related\_name = "citizen") def __unicode__(self): return self.firstname + self.lastname
PS:
注1：创建的app名为“QSOptimize”注2：为了简化起见，qsoptimize_province 表中只有2条数据：湖北省和广东省，qsoptimize_city表中只有三条数据：武汉市、十堰市和广州市
一些实例
选择哪些函数
如果我们想要获得所有家乡是湖北的人，最无脑的做法是先获得湖北省，再获得湖北的所有城市，最后获得故乡是这个城市的人。就像这样：
>>> 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。
prefetch_related() 或许是一个好的解决方法，让我们来看看。>>> 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);
嗯…看上去不错，但是3次查询么？倒过来查询可能会更简单？
>>> 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。
select_related()的效率要高于prefetch_related()。因此，最好在能用select_related()的地方尽量使用它，也就是说，对于ForeignKey字段，避免使用prefetch_related()。联用
对于同一个QuerySet，你可以同时使用这两个函数。
在我们一直使用的例子上加一个model：Order （订单）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)
更好的办法是先调用一次select_related()再调用prefetch_related()，最后再select_related()后面的表
>>> 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。
总结
- 因为select_related()总是在单次SQL查询中解决问题，而prefetch_related()会对每个相关表进行SQL查询，因此select_related()的效率通常比后者高。
- 鉴于第一条，尽可能的用select_related()解决问题。只有在select_related()不能解决问题的时候再去想prefetch_related()。
- 你可以在一个QuerySet中同时使用select_related()和prefetch_related()，从而减少SQL查询的次数。
- 只有prefetch_related()之前的select_related()是有效的，之后的将会被无视掉。