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
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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 ())
...
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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 ())
...
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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 );
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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)
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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
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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
...
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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)
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| id | firstname | lastname | hometown_id | living_id |
+ - - - - + - - - - - - - - - - - + - - - - - - - - - - + - - - - - - - - - - - - - + - - - - - - - - - - - +
| 1 | 张 | 三 | 3 | 1 |
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1 row in set ( 0.00 sec)
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| _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 |
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3 rows in set ( 0.00 sec)
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| id | name |
+ - - - - + - - - - - - - - +
| 1 | 湖北省 |
| 2 | 广东省 |
+ - - - - + - - - - - - - - +
2 rows in set ( 0.00 sec)
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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
...
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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)
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| _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)
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| id | name |
+ - - - - + - - - - - - - - +
| 1 | 湖北省 |
| 2 | 广东省 |
+ - - - - + - - - - - - - - +
2 rows in set ( 0.00 sec)
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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。