MongoDB初探-介绍与环境搭建
一、简介 随着互联网web2.0网站的兴起,传统的关系数据库在应付web2.0网站,特别是超大规模和高并发的SNS类型的web2.0纯动态网站已经显得力不从心,暴露了很多难以克服的问题,而非关系型的数据库则由于其本身的特点得到了非常迅速的发展。MongoDB非凡的表现
一、简介
随着互联网web2.0网站的兴起,传统的关系数据库在应付web2.0网站,特别是超大规模和高并发的SNS类型的web2.0纯动态网站已经显得力不从心,暴露了很多难以克服的问题,而非关系型的数据库则由于其本身的特点得到了非常迅速的发展。MongoDB非凡的表现使其在NoSQL中占有重要地位,当然其他的NoSQL数据库,比如CouchDB,Redis,Hbase等也各有千秋。本系列将带领大家领略MongoDB的魅力。
1、MongoDB是什么?
MongoDB是一种强大,灵活,可扩展的数据存储方式。它扩展了关系型数据库的众多有用功能,如辅助索引,范围查询(range query)和排序。MongoDB的功能非常丰富,比如内置的对MapReduce式聚合的支持,以及对地理空间索引的支持。
2、为什么使用MongoDB?
2.1、丰富的数据模型。由于MongoDB没有模式,所以支持的数据模型也就相等丰富(基本支持现实生活中的所有数据模型),并且容易变更。
2.2、容易扩展。MongoDB采用的面向文档的数据模型使其可以自动在多台服务器之间分割数据,它还可以平衡集群的数据和负载,自动重排文档。如果需要扩充容量,只需在集群中添加新机器即可。
2.3、丰富的功能。
2.3.1、索引。MongoDB支持通用辅助索引,能进行多种快速查询,也提供唯一的,复合的和地理空间索引能力。
2.3.2、存储JavaScript。开发人员可以支持在服务器端存取JavaScript的函数和值,而不用使用关系型数据库中的存储过程。
2.3.3、聚合。MongoDB支持MapReduce和其他聚合工具,这为云计算提供支持。
2.3.4、固定集合。集合的大小有上限,这对某些类型的数据(比如日志)特别有用。
2.3.5、文件存储。MongoDB支持用BSON(Binary JSON)格式的协议存储大型文件和文件的元数据。
2.4、卓越的性能。MongoDB使用MongoDB传输协议作为与服务器交互的主要方式,比HTTP/REST协议要节省很多开销。默认存储引擎使用内存映射文件,将内存管理工作交给操作系统处理。
2.5、管理方便。MongoDB通过尽可能的让服务器自动配置来简化数据库服务器的管理,比如主/备切换,集成环境新节点的集成和配置等。
二、安装与启动
1、MongoDB安装很简单,只需要根据操作系统的版本从官网http://www.mongodb.org/downloads上下载对应的二进制压缩包,解压,执行安装即可。可以将MongoDB的bin路径放到PATH变量中,这样方便从控制台访问MongoDB。
2、创建数据库文件存放目录,默认为C:\data\db.如果不是默认目录,则需要在启动MongoDB时指定数据目录。
3、打开命令提示(cmd.exe),进入MongoDB解压目录下(如果加入PATH时可以省略),然后执行
bin/mongod.exe如果使用的不是默认目录(C:\data\db)则需要使用--dbpath参数指定:
>mongod --dbpath E:\Study\MongoDB\db三、将MongoDB作为服务安装
使用--install参数将MongoDB作为服务安装,如下:
>mongod --dbpath "\"E:\Study\MongoDB\db\"" --install

The steps to create and manage user accounts in MySQL are as follows: 1. Create a user: Use CREATEUSER'newuser'@'localhost'IDENTIFIEDBY'password'; 2. Assign permissions: Use GRANTSELECT, INSERT, UPDATEONmydatabase.TO'newuser'@'localhost'; 3. Fix permission error: Use REVOKEALLPRIVILEGESONmydatabase.FROM'newuser'@'localhost'; then reassign permissions; 4. Optimization permissions: Use SHOWGRA

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MySQL's performance under high load has its advantages and disadvantages compared with other RDBMSs. 1) MySQL performs well under high loads through the InnoDB engine and optimization strategies such as indexing, query cache and partition tables. 2) PostgreSQL provides efficient concurrent read and write through the MVCC mechanism, while Oracle and Microsoft SQLServer improve performance through their respective optimization strategies. With reasonable configuration and optimization, MySQL can perform well in high load environments.

InnoDBBufferPool reduces disk I/O by caching data and indexing pages, improving database performance. Its working principle includes: 1. Data reading: Read data from BufferPool; 2. Data writing: After modifying the data, write to BufferPool and refresh it to disk regularly; 3. Cache management: Use the LRU algorithm to manage cache pages; 4. Reading mechanism: Load adjacent data pages in advance. By sizing the BufferPool and using multiple instances, database performance can be optimized.

Compared with other programming languages, MySQL is mainly used to store and manage data, while other languages such as Python, Java, and C are used for logical processing and application development. MySQL is known for its high performance, scalability and cross-platform support, suitable for data management needs, while other languages have advantages in their respective fields such as data analytics, enterprise applications, and system programming.

MySQL is worth learning because it is a powerful open source database management system suitable for data storage, management and analysis. 1) MySQL is a relational database that uses SQL to operate data and is suitable for structured data management. 2) The SQL language is the key to interacting with MySQL and supports CRUD operations. 3) The working principle of MySQL includes client/server architecture, storage engine and query optimizer. 4) Basic usage includes creating databases and tables, and advanced usage involves joining tables using JOIN. 5) Common errors include syntax errors and permission issues, and debugging skills include checking syntax and using EXPLAIN commands. 6) Performance optimization involves the use of indexes, optimization of SQL statements and regular maintenance of databases.


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