使用Django从数据库中随机取N条记录的不同方法及其性能实测
【声明】：本文中的实验仅限于特定数据库和特定框架。不同数据库，数据库服务器的性能，甚至同一个数据库的不同配置都会影响到同一段代码的性能。具体情况请在自己的生产环境进行测试。
这里（stackoverflow）有一篇关于使用Django随机获取记录的讨论。主要意思是说
Python
1 | Record.objects.order_by('?')[:2] |
这样获取2个记录会导致性能问题，原因如下：
“ 对于有着相当多数量记录的表来说，这种方法异常糟糕。这会导致一个 ORDER BY RAND() 的SQL查询。举个栗子，这里是MYSQL是如何处理这个查询的（其他数据库的情况也差不多），想象一下当一个表有十亿行的时候会怎样：
为了完成ORDER BY RAND() ，需要一个RAND()列来排序
为了有RAND()列，需要一个新表，因为现有的表没有这个列。
为了这个新表，mysql建立了一个带有新列的，新的临时表，并且将已有的一百万行数据复制进去。
当其新建完了，他如你所要求的，为每一行运行RAND()函数来填上这个值。是的，你派mysql创建一百万个随机数，这要点时间：）
几个小时或几天后，当他干完这活，他要排序。是的，你排mysql去排序一个一百万行的，最糟糕的表（说他最糟糕是因为排序的键是随机的）。
几天或者几星期后，当排序完了，他忠诚地将你实际需要的可怜的两行抓出来返回给你。做的好。；）
注意：只是稍微说一句，得注意到mysql一开始会试着在内存中创建临时表。当内存不够了，他将会把所有东西放在硬盘上，所以你会因为近乎于整个过程中的I/O瓶颈而雪上加霜。
怀疑者可以去看看python代码引起的查询语句，确认是ORDER BY RAND()， 然后去Google下”order by rand()”（带上引号）。
一个更好的方式是将这个耗费严重的查询换成3个耗费更轻的：
Python
1 2 3 4 5 6 7 8 | last = MyModel.objects.count() - 1 # 这是一个获取两个不重复随机数的简单方法 index1 = randint(0, last) index2 = randint(0, last - 1) if index2 == index1: index2 = last MyObj1 = MyModel.objects.all()[index1] MyObj2 = MyModel.objects.all()[index2] |
”
如上Manganeez所说的方法，相应的获取n条记录的代码应该如下：
Python
1 2 | sample = random.sample(xrange(Record.objects.count()),n) result = [Record.objects.all()[i] for i in sample] |
基于Python代码应该简洁优雅的想法，如上的代码似乎可以写成：
Python
1 | result = random.sample(Record.objects.all(),n) |
就性能问题，请教了stackoverflow上的大神 （虽然被踩和被教育了=。=）
“Record.objects.count() 将被转换成一个相当轻量级的SQL请求：
MySQL
1 | SELECT COUNT(*) FROM TABLE |
Record.objects.all()[0]也会被转换成一个十分轻量级的SQL请求
MySQL
1 | SELECT * FROM TABLE LIMIT 1 |
Querying all 是一个耗费十分严重的请求
MySQL
1 | SELECT * FROM TABLE |
通常情况下Django会不显示其他的结果，这样你不会真正的获取到所有的记录。
Python
1 | SELECT * FROM table LIMIT 20; // or something similar |
任何时候你将一个Queryset转换成list的时候，将是资源消耗严重的时候。
如果我没错的话，在这个例子里，sample方法将把Queryset转换成list。
这样如果你result = random.sample(Record.objects.all(),n) 这样做的话，全部的Queryset将会转换成list，然后从中随机选择。
想象一下如果你有十亿行的数据。你是打算把它存储在一个有百万元素的list中，还是愿意一个一个的query？
”
在上边Yeo的回答中，freakish回复道：“.count的性能是基于数据库的。而Postgres的.count为人所熟知的相当之慢。”
某人说过，要知道梨子的滋味，就得变革梨子，亲口尝一尝。
测试环境：
Win8.1 pro x64
Wampserver2.4-x64 (apache2.4.4 mysql5.6.12 php5.4.12)
Python2.7.5
Django1.4.6
在一个已有的测试project中新建一个app，数据库是MYSQL：
1 | D:\PyWorkspace\DjangoTest>python manage.py startapp randomrecords |
在models.py中添加模型：
Python
1 2 3 4 5 6 7 8 9 10 | class Record(models.Model): """docstring for Record"""
id = models.AutoField(primary_key = True) content = models.CharField(max_length = 16)
def __str__(self): return "id:%s content:%s" % (self.id, self.content) def __unicode__(self): return u"id:%s content:%s" % (self.id, self.content) |
添加一万行数据：
Python
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | D:\PyWorkspace\DjangoTest>python manage.py syncdb Creating tables ... Creating table randomrecords_record Installing custom SQL ... Installing indexes ... Installed 0 object(s) from 0 fixture(s)
D:\PyWorkspace\DjangoTest>python manage.py shell Python 2.7.5 (default, May 15 2013, 22:44:16) [MSC v.1500 64 bit (AMD64)] on win 32 Type "help", "copyright", "credits" or "license" for more information. (InteractiveConsole) >>> from randomrecords.models import Record >>> for i in xrange(10000): ... Record.objects.create(content = 'c of %s' % i).save() |
15分钟以后我得到了这个MYSQL表。真的，不骗你，真的是15分钟。看了记录才知道 每次save都要调用一次insert和一次update。。。。下次一定用SQL语句初始化。。。。
先写了个脚本 在manage.py shell中调用了下 结果让我震惊了。我表示不敢相信 又写了view 并在settings.py中添加了显示SQL Query语句的log
这里是写的view：
Python
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | def test1(request): start = datetime.datetime.now() result = Record.objects.order_by('?')[:20] l = list(result) # Queryset是惰性的，强制将Queryset转为list end = datetime.datetime.now() return HttpResponse("time: <br/> %s" % (end-start).microseconds/1000))
def test2(request): start = datetime.datetime.now() sample = random.sample(xrange(Record.objects.count()),20) result = [Record.objects.all()[i] for i in sample] l = list(result) end = datetime.datetime.now() return HttpResponse("time: <br/> %s" % (end-start)
def test3(request): start = datetime.datetime.now() result = random.sample(Record.objects.all(),20) l = list(result) end = datetime.datetime.now() return HttpResponse("time: <br/> %s" % (end-start) |
运行结果如下，第一行是页面显示的时间，后边是Queryset实际调用的SQL语句
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | test1：
time: 0:00:00.012000
(0.009) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` ORDER BY RAND() LIMIT 20; args=() [05/Dec/2013 17:48:19] "GET /dbtest/test1 HTTP/1.1" 200 775
test2:
time: 0:00:00.055000
(0.002) SELECT COUNT(*) FROM `randomrecords_record`; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 6593; args=() (0.001) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 2570; args=() (0.001) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 620; args=() (0.001) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 5814; args=() (0.003) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 6510; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 3536; args=() (0.001) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 3362; args=() (0.003) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 8948; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 7723; args=() (0.001) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 2374; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 8269; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 4370; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 6953; args=() (0.001) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1441; args=() (0.000) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 772; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 4323; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 8139; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 7441; args=() (0.001) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1306; args=() (0.001) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 5462; args=() [05/Dec/2013 17:50:34] "GET /dbtest/test2 HTTP/1.1" 200 777
test3:
time: 0:00:00.156000
(0.032) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record`; args=() [05/Dec/2013 17:51:29] "GET /dbtest/test3 HTTP/1.1" 200 774 |
令人难以置信的，在10000行的MYSQL表中 方法1的效率是最高的。无论是结果上看（12ms）还是SQL语句的运行时间上看（9ms）方法1甩了其他方法一大截
即便数据量增加到21万，方法1也会比其他两种方法快：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | time: 98
(0.094) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` ORDER BY RAND() LIMIT 20; args=() [05/Dec/2013 19:18:59] "GET /dbtest/test1 HTTP/1.1" 200 14
time: 0:00:00.668000 //这里没有注意到 掉了一行count语句 (0.045) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 176449; args=() (0.016) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 68082; args=() (0.036) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 145571; args=() (0.033) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 111029; args=() (0.043) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 169675; args=() (0.046) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 186234; args=() (0.043) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 167233; args=() (0.015) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 54404; args=() (0.036) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 140395; args=() (0.004) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 13128; args=() (0.039) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 153695; args=() (0.034) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 131863; args=() (0.021) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 82785; args=() (0.015) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 57253; args=() (0.021) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 77836; args=() (0.049) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 199567; args=() (0.002) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 3867; args=() (0.027) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 104470; args=() (0.026) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 107058; args=() (0.043) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 150979; args=() [05/Dec/2013 19:21:33] "GET /dbtest/test2 HTTP/1.1" 200 15
time 0:00:00.781000
[05/Dec/2013 19:23:01] "GET /dbtest/test3 HTTP/1.1" 200 15 (0.703) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record`; args=() [05/Dec/2013 19:23:06] "GET /dbtest/test3 HTTP/1.1" 200 15 |
数据量再次提升至百万级别 1066768条数据
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | time: 0:00:02.197000
(2.193) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` ORDER BY RAND() LIMIT 20; args=() [05/Dec/2013 20:00:55] "GET /dbtest/test1 HTTP/1.1" 200 26
time: 0:00:02.659000
(0.204) SELECT COUNT(*) FROM `randomrecords_record`; args=() (0.180) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 703891; args=() (0.038) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 156668; args=() (0.013) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 50742; args=() (0.031) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 121107; args=() (0.033) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 130565; args=() (0.017) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 66225; args=() (0.234) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 922479; args=() (0.267) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1027166; args=() (0.189) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 765499; args=() (0.009) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 31569; args=() (0.233) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 934055; args=() (0.264) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1052741; args=() (0.155) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 621692; args=() (0.014) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 52388; args=() (0.199) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 759669; args=() (0.170) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 655598; args=() (0.035) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 139709; args=() (0.228) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 919480; args=() (0.104) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 422051; args=() (0.017) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 67549; args=() [05/Dec/2013 20:00:45] "GET /dbtest/test2 HTTP/1.1" 200 26
time: 0:00:19.651000
(3.645) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record`; args=() [05/Dec/2013 20:02:50] "GET /dbtest/test3 HTTP/1.1" 200 26 |
第三种方法所用时间长到令人无法接受（19.65秒）。但有意思的是 SQL语句所花费的时间“只有”3.6秒。而大部分的时间都用在python上了。
既然第二种方法和第三种方法都需要random.sample 一个百万个数据的list，那就是说，有大量的时间花费在将SELECT到的结果转化为django对象的过程中了。
此后将不再测试第三种方法
最后，数据量增加到5,195,536个
随着表中数据行数的增加，两个方法的所用的时间都到了一个完全不能接受的程度。两种方法所用的时间也几乎相同。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | time: 0:00:22.278000
(22.275) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FR OM `randomrecords_record` ORDER BY RAND() LIMIT 20; args=() [05/Dec/2013 21:46:33] "GET /dbtest/test1 HTTP/1.1" 200 26
time: 0:00:33.319000
(1.393) SELECT COUNT(*) FROM `randomrecords_record`; args=() (3.201) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 4997880; args=() (1.229) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 2169311; args=() (0.445) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1745307; args=() (1.306) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 3233861; args=() (1.881) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 3946647; args=() (1.624) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 3534377; args=() (1.068) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1684337; args=() (0.902) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 2607361; args=() (2.938) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 4872494; args=() (0.493) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 851494; args=() (3.275) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 5182414; args=() (0.946) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1684670; args=() (0.701) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1819730; args=() (0.915) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1626221; args=() (1.809) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 3638682; args=() (3.237) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 4801027; args=() (1.187) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1955843; args=() (2.736) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 4835733; args=() (1.705) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 2756641; args=() (0.286) SELECT `randomrecords_record`.`id`, `randomrecords_record`.`content` FRO M `randomrecords_record` LIMIT 1 OFFSET 1117426; args=() |
值得注意的是，Mysql数据库有一个特点是，对于一个大表，OFFSET越大，查询时间越长。或许有其他方法可以在offset较大的时候加快select的速度，然而django明显没有做到。如果能够减少这种消耗，方法2明显会优于方法1。
附上三种方法数据量和SQL时间/总时间的数据图表：
最后总结，Django下，使用mysql数据库，数据量在百万级以下时，使用
Python
1 | Record.objects.order_by('?')[:2] |
来获取随机记录序列，性能不会比
Python
1 2 | sample = random.sample(xrange(Record.objects.count()),n) result = [Record.objects.all()[i]) for i in sample] |
差。
