Python 置顶 superman 07月31日 15:53 157

【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

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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:

  1. 为了完成ORDER BY RAND() ,需要一个RAND()列来排序

  2. 为了有RAND()列,需要一个新表,因为现有的表没有这个列。

  3. 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。

  4. 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:)

  5. 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)。

  6. 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:

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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:

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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:

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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

 

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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

 

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SELECT * FROM TABLE LIMIT 1

Querying all 是一个耗费十分严重的请求

MySQL

 

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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。

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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:

 

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D:\PyWorkspace\DjangoTest>python manage.py startapp randomrecords

在models.py中添加模型:

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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:

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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:

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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

 

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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:

 

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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

 

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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&ldquo;只有&rdquo;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。

 

 

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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:

table

20131205220333

总时间

 

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。

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