实例的背景说明
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 内容如下:
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from django.db import models class Province(models.Model): name = models.CharField(max_length = 10 ) def __unicode__( self ): return self .name class City(models.Model): name = models.CharField(max_length = 5 ) province = models.ForeignKey(Province) def __unicode__( self ): return self .name class 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 |
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
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:
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>>> 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。
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>>> 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:
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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?
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>>> 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)
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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?
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>>> 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
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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 ); |
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+ - - - - + - - - - - - - - - - - - - + - - - - - - - - - - - - - - - + - - - - - - - - - - - - - - - - - - - - - + | 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
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>>> 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:
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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。
小结
- 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。