實例的背景說明
假定一個個人信息系統，需要記錄系統中各個人的故鄉、居住地、以及到過的城市。數據庫設計如下：
Models.py 內容如下：
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：創建的app名為“QSOptimize”
注2：為了簡化起見，`qsoptimize_province` 表中只有2條數據：湖北省和廣東省，`qsoptimize_city`表中只有三條數據：武漢市、十堰市和廣州市
如果我們想要獲得所有家鄉是湖北的人，最無腦的做法是先獲得湖北省，再獲得湖北的所有城市，最后獲得故鄉是這個城市的人。就像這樣：
>>> hb = Province.objects.get(name__iexact=u"湖北省")>>> people = []>>> for city in hb.city_set.all():... people.extend(city.birth.all())...
顯然這不是一個明智的選擇，因為這樣做會導致1+（湖北省城市數）次SQL查詢。反正是個反例，導致的查詢和獲得掉結果就不列出來了。
prefetch_related() 或許是一個好的解決方法，讓我們來看看。
>>> 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())...因為是一個深度為2的prefetch，所以會導致3次SQL查詢：
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…看上去不錯，但是3次查詢么？倒過來查詢可能會更簡單？
>>> 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 | 張 | 三 | 3 | 1 | 3 | 十堰市 | 1 | 1 | 湖北省 || 2 | 李 | 四 | 1 | 3 | 1 | 武漢市 | 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)完全沒問題。不僅SQL查詢的數量減少了，python程序上也精簡了。
select_related()的效率要高于prefetch_related()。因此，最好在能用select_related()的地方盡量使用它，也就是說，對于ForeignKey字段，避免使用prefetch_related()。
聯用
對于同一個QuerySet，你可以同時使用這兩個函數。
在我們一直使用的例子上加一個model：Order （訂單）
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
如果我們拿到了一個訂單的id 我們要知道這個訂單的客戶去過的省份。因為有ManyToManyField顯然必須要用prefetch_related()。如果只用prefetch_related()會怎樣呢？
>>> plist = Order.objects.prefetch_related('customer__visitation__province').get(id=1)>>> for city in plist.customer.visitation.all():... print city.province.name...顯然，關系到了4個表：Order、Person、City、Province，根據prefetch_related()的特性就得有4次SQL查詢
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 | 張 | 三 | 3 | 1 |+----+-----------+----------+-------------+-----------+1 row in set (0.00 sec) +-----------------------+----+--------+-------------+| _prefetch_related_val | id | name | province_id |+-----------------------+----+--------+-------------+| 1 | 1 | 武漢市 | 1 || 1 | 2 | 廣州市 | 2 || 1 | 3 | 十堰市 | 1 |+-----------------------+----+--------+-------------+3 rows in set (0.00 sec) +----+--------+| id | name |+----+--------+| 1 | 湖北省 || 2 | 廣東省 |+----+--------+2 rows in set (0.00 sec)
更好的辦法是先調用一次select_related()再調用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...這樣只會有3次SQL查詢，Django會先做select_related，之后prefetch_related的時候會利用之前緩存的數據，從而避免了1次額外的SQL查詢：
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 | 張 | 三 | 3 | 1 |+----+-------------+---------------+---------------------+----+-----------+----------+-------------+-----------+1 row in set (0.00 sec) +-----------------------+----+--------+-------------+| _prefetch_related_val | id | name | province_id |+-----------------------+----+--------+-------------+| 1 | 1 | 武漢市 | 1 || 1 | 2 | 廣州市 | 2 || 1 | 3 | 十堰市 | 1 |+-----------------------+----+--------+-------------+3 rows in set (0.00 sec) +----+--------+| id | name |+----+--------+| 1 | 湖北省 || 2 | 廣東省 |+----+--------+2 rows in set (0.00 sec)
值得注意的是，可以在調用prefetch_related之前調用select_related，并且Django會按照你想的去做：先select_related，然后利用緩存到的數據prefetch_related。然而一旦prefetch_related已經調用，select_related將不起作用。
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