实例详解Django的 select_related 和 prefetch_related 函数对 QuerySet 查询的优化（三）...-白红宇

实例详解Django的 select_related 和 prefetch_related 函数对 QuerySet 查询的优化（三）...

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发布时间：2019-06-29

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这是本系列的最后一篇，主要是select_related() 和 prefetch_related() 的最佳实践。

第一篇在讲例子和select_related()

第二篇在讲prefetch_related()

4. 一些实例

选择哪个函数

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。

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

转载于:https://www.cnblogs.com/stevenzeng/p/5163527.html

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