实现一个微型数据库
自己写一个简单的数据库, 原理 大概有以下几点: 一、数据以文本形式保存 将所要保存的数据写入文本文件,这个文本文件就是数据库。 为了方便读取,数据必须分为记录,每一条记录的长度规定为等长。 举例:假定每条记录的长度是800字节,那么第5条记录的开
自己写一个简单的数据库,原理大概有以下几点:
一、数据以文本形式保存
将所要保存的数据写入文本文件,这个文本文件就是数据库。
为了方便读取,数据必须分为记录,每一条记录的长度规定为等长。
举例:假定每条记录的长度是800字节,那么第5条记录的开始位置就在3200字节。
大多数的时候我们不知道某一条记录在第几个位置,只知道主键的值。这时为了读取数据,可以一条条比对记录。但是这样做的效率太低。实际应用中,数据库往往采用B树格式存储数据。
二、关于B树
要理解B树先需要理解二叉查找树
说二叉查找树是一种查找效率非常高的数据结构,它有三个特点:
(1)每个节点最多只有两个子树。
(2)左子树都为小于父节点的值,右子树都为大于父节点的值。
(3)在n个节点中找到目标值,一般只需要log(n)次比较。
二叉查找树的结构不适合数据库,因为他的查找效率与层数有关。越处在下层的数据,就需要越多次的比较。极端的情况下,n个数据需要n次比较才能找到目标值。对于数据库来说,每进入一层,就要从硬盘读取一次数据,这非常致命,因为硬盘的读取时间远远大于数据处理时间,数据库读取硬盘的次数越少越好。
B树是对二叉查找树的改进。它的设计思想是,将相关数据尽量集中在一起,以便一次读取多个数据,减少硬盘操作次数。
B树的特点:
(1)一个节点可以容纳多个值。
(2)除非数据已经填满,否则不会增加新的层,也就是说,B树追求“层”越少越好。
(3)子节点的值,与父节点中的值有严格的大小对应关系。一般来说,如果父节点有a个值,那么就有a+1个子节点。比如上图中,父节点有两个值(7和16),就应对应三个子节点,第一个子节点都是小于7的值,最后一个子节点都是大于16的值,中间的子节点就是7和16之间的值。
这种数据结构非常有利于减少读取硬盘的次数。假定一个节点可以容纳100个值,那么3层的B树可以容纳100万个数据,如果换成二叉查找树,则需要20层。假定操作系统一次读取一个节点,并且根节点保留在内存中,那么B树在100万个数据中查找目标值,只需要读取两次硬盘。
三、索引
数据库以B树格式存储,只解决了按照“主键”查找数据的问题。如果想查找其他字段,就需要建立检索(index)。
所谓索引,就是以某个字段为关键字的B树文件,假定一张“雇员表”,包含了员工号(主键)和姓名两个字段,可以对姓名建立索引文件,该文件以B树格式对姓名进行存储,每个姓名后面是其在数据库中的位置(即第几条记录)。查找姓名的时候,先从索引中找到对应的第几条记录,然后再从表格中读取。这种索引查找方法,叫做“索引顺序存取方法”,缩写为ISAM。它已经有多种实现,只要使用这些代码库,就能自己写一个最简单的数据库。
四、高级功能
部署了最基本的数据存取(包括索引)以后,还可以实现一些高级功能。
(1)SQL语言是数据库通用操作语言,所以需要一个SQL解析器,将SQL命令解析为对应的ISAM操作。
(2)数据库连接(join)是指数据库的两张表通过“外键”,建立连接关系。你需要对这种操作进行优化。
(3)数据库事务(transaction)是指批量进行一系列数据库操作,只要有一步不成功,整个操作都不成功。所以需要有一个“操作日志”,以便失败时对操作进行回滚。
(4)备份机制:保存数据库的副本。
(5)远程操作:使得用户可以在不同的机器上,通过TCP/IP协议操作数据库。
部分内容来自点击打开链接,后续依然会不断更新完善。

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