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1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust


  新智元报道  

来源：Avinash

一位程序员急需在一分钟之内生成十亿行的测试数据库，然而在用Python写了脚本之后发现「大失败」。怎么办？当然是用Rust了！
 
于是，他做了一个所有程序员都会做的事：写一个Python脚本来生成数据库。
 
然而，很不幸的是，这个脚本非 常 慢。
 
1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust
 
于是，他又做了一个所有程序员都会做的事：进一步学习关于SQLite、Python以及不知道为什么还有Rust的知识。

项目已开源：https://github.com/avinassh/fast-sqlite3-inserts
 

目标



作者需要在他2019年的MacBook Pro（2.4GHz四核i5）上，一分钟内生成一个有10亿行的SQLite数据库。
 

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust

表的模式
 
要求：

  1. 生成的数据是随机的；


  2. 「area」列将包含六位数的地区代码（任何六位数都可以，不需要验证）；


  3. 「age」列是5、10或15中的任何一个；


  4. 「active」列是0或1。

 
不过，作者表示，对脚本的要求也不用太高，还是可以妥协的：

  1. 如果进程崩溃，所有的数据都丢失也没有问题，再次运行脚本就可以了；


  2. 允许充分利用电脑的资源：100%的CPU，8GB的内存和剩余的SSD储存；


  3. 不需要使用真正的随机方法，来自stdlib的伪随机方法就可以。


Python原型


在最开始的脚本中，作者试图在一个for循环中逐一插入1000万条记录，而这让用时直接达到了15分钟。
 
1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust
 
显然，这太慢了。
 
在SQLite中，每次插入都是一个事务，每个事务都保证它被写入磁盘，作者推断可能问题就来自这里。
 
于是作者开始尝试不同规模的批量插入，发现10万是一个最佳点，而运行时间减少到了10分钟。
 

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust

 

SQLite优化


作者认为自己写的代码已经很简练了，并没有什么可以优化的空间。

于是他将下一个目标转到了数据库的优化。
 
根据各种关于SQLite优化的建议，作者做了一些改进。
 

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust

 

  • 关闭「journal_mode」将禁用回滚日志，也就是说，如果任何事务失败，都无法回滚。


  • 关闭「synchronous」，将使SQLite不再关心是否能可靠地写入磁盘，而是把这个责任交给操作系统。也就是说，可能会出现SQLite并没有成功写入磁盘的情况。


  • 「cache_size」指定了SQLite在内存中可以保留多少个内存页。


  • 当「locking_mode」为「EXCLUSIVE」模式时，SQLite锁住的连接将永远不会被释放。


  • 将「temp_store」设置为「MEMORY」可以让其表现像一个内存数据库。


此处作者提醒，请不要把这些操作用到生产上去。


重新审视Python


作者再次重写了Python脚本，这次包括了微调的SQLite参数，这次带来了巨大的提升，运行时间大幅减少：

  • 原始的for循环版本用时大约10分钟。


  • 批处理版本用时大约8.5分钟。

 

PyPy


PyPy在其主页上强调它比CPython快4倍，于是作者决定尝试一下。
 
令作者有些意外的是，竟然不需要对现有的代码进行任何改动，只需要在PyPy运行就可以了。
 
批处理版本只需要2.5分钟，也就是速度快了接近3.5倍。
 

Busy Loop？


莫非是在Python的循环上耗费了太多时间？于是作者删除了SQL指令之后再次跑了一遍代码：

  • 批处理版本在CPython中用时5.5分钟。

 

  • 批处理版本在PyPy中用时1.5分钟（又是3.5倍的速度提升）。


然而用Rust重写了相同的内容之后，循环只需要17秒。

于是，作者果断抛弃Python，转投Rust的怀抱。
 

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust

  

Rust


像Python一样，作者先写了一个原始的Rust版本，一个循环执行一行数据的插入。

然而，即便使用了所有SQLite的优化，也依然消耗了大约3分钟。于是作者进行了进一步的测试：
 

  • 尝试把「rusqlite」换成异步运行的「sqlx」，这让用时直接被拉到了14分钟。作者表示，这比自己迄今为止写的任何一个Python迭代都要差。


  • 在执行原始SQL语句时，使用准备好的语句。这个版本的用时只有1分钟。

 

最优的版本


使用准备好的语句，以50行为一个批次插入，最终用时34.3秒。
 
作者又写了一个线程版本，其中一个线程从通道接收数据，还有四个线程向通道推送数据。
 
这个也是目前性能最好的版本，最终用时大约32.37秒。
 

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust


IO时间


SQLite论坛上的网友提出了一个有趣的想法：测量内存数据库所需的时间。
 
于是作者又跑了一遍代码，将数据库的位置设定为「:memory:」，rust版本完成的时间少了两秒（29秒）。
 
也就是说将1亿条记录写入到磁盘上需要2秒，这个用时似乎也是合理的。
 
这也说明，可能没有更多的SQLite优化可以以更快的方式写入磁盘，因为99%的时间都花在生成和添加数据上。
 

排行榜


插入1亿行数据的用时：

Rust 33秒
PyPy 126秒
CPython 210秒


总结


  1. 尽可能使用SQLite PRAGMA语句
 
  1. 使用准备好的语句
 
  1. 进行分批插入
 
  1. PyPy确实比CPython快4倍
 
  1. 异步不一定更快


目前，第二快的版本是单线程运行的，而作者的电脑有4个核心，于是他在一分钟内可以得到8亿行数据。然后再经过几秒钟的数据合并，时间仍然可以少于一分钟。


网友评论


博主的这一番研究获得了网友们的一致好评。


1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust

真的很喜欢这些观点：
  1. 学习了更多关于PRAGMA语句。
  2. PyPy的效率和灵活性可以通过即插即用的方式体现（将来一定会给它一个机会）。
  3. 文章的排版非常简单，有适当的源代码链接。很有趣，很容易上手。


Rust高光时刻又来了！

福利



入门Python的最强三件套《ThinkPython》、《简明Python教程》、《Python进阶》的PDF电子版已打包提供给大家，关注下方，在后台回复关键字「P3」即可获取。

1分钟插入10亿行数据！抛弃Python，写脚本请使用Rust




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  • 2).学Python真香！我用100行代码做了个网站，帮人PS旅行图片，赚个鸡腿吃

  • 3).首播过亿，火爆全网，我分析了《乘风破浪的姐姐》，发现了这些秘密 

  • 4).80行代码！用Python做一个哆来A梦分身 

  • 5).你必须掌握的20个python代码，短小精悍，用处无穷 

  • 6).30个Python奇淫技巧集 

  • 7).我总结的80页《菜鸟学Python精选干货.pdf》,都是干货 

  • 8).再见Python！我要学Go了！2500字深度分析！

  • 9).发现一个舔狗福利！这个Python爬虫神器太爽了，自动下载妹子图片


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data-darkmode-original-bgcolor-15870356071023="rgb(255, 255, 255)" data-darkmode-color-15870356071023="rgb(51, 51, 51)" data-darkmode-original-color-15870356071023="rgb(51, 51, 51)" data-darkmode-bgimage-15870356071023="1" data-darkmode-bgcolor-15882384789136="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15882384789136="rgb(255, 255, 255)" data-darkmode-color-15882384789136="rgb(51, 51, 51)" data-darkmode-original-color-15882384789136="rgb(51, 51, 51)" data-darkmode-bgimage-15882384789136="1" data-darkmode-bgcolor-15882396318564="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15882396318564="rgb(255, 255, 255)" data-darkmode-color-15882396318564="rgb(51, 51, 51)" data-darkmode-original-color-15882396318564="rgb(51, 51, 51)" data-darkmode-bgimage-15882396318564="1" data-darkmode-bgcolor-15900529136199="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15900529136199="rgb(255, 255, 255)" data-darkmode-color-15900529136199="rgb(51, 51, 51)" data-darkmode-original-color-15900529136199="rgb(51, 51, 51)" data-darkmode-bgimage-15900529136199="1" style="max-width: 100%;font-size: 14px;color: rgb(51, 51, 51);text-align: left;box-sizing: border-box !important;overflow-wrap: break-word !important;"><span style="max-width: 100%;font-family: 楷体, 楷体_GB2312, SimKai;white-space: pre-wrap;font-size: 12px;box-sizing: border-box !important;overflow-wrap: break-word !important;">点阅读原文,领优惠券！</span></section></section></section></section></section></section></section>

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