MongoDB安装及做成服务 安装及使用: www.2cto.com 首先在Ubuntu上安装MongoDB。 下载MongoDB, 现在最新的生产版本1.7.0 1. 解压文件. $ tar -xvf mongodb-linux-i686-1.4.3.tgz 2. 为MongoDB创建数据目录,默认情况下它将数据存储在/data/db $ sudo mkdir -
MongoDB安装及做成服务
安装及使用:
www.2cto.com
首先在Ubuntu上安装MongoDB。
下载MongoDB, 现在最新的生产版本1.7.0
1. 解压文件.
$ tar -xvf mongodb-linux-i686-1.4.3.tgz
2. 为MongoDB创建数据目录,默认情况下它将数据存储在/data/db
$ sudo mkdir -p /data/db/
$ sudo chown `id -u` /data/db
3. 启动MongoDB服务.
$ cd mongodb-linux-i686-1.4.3/bin
$ ./mongod
4. 打开另一个终端,并确保你在MongoDB的bin目录,输入如下命令.
$ ./mongo
====================================================================
每次开机运行都需要在(cmd)下面手动输入
E
cd E:\APMServ5.2.6\MongoDb\bin
mongod --dbpath E:\APMServ5.2.6\MongoDb\data
这样感觉非常麻烦,所以将Mongo数据库安装成为Windows服务。如此就方便很多啦
E:\APMServ5.2.6\MongoDb\bin>mongod --logpath E:\APMServ5.2.6\MongoDb\logs\MongoDB.log --logappend --dbpath E:\APMServ5.2.6\MongoDb\data --directoryperdb --serviceName MongoDB --install
回车显示如下便是服务安装成功
all output going to: E:\APMServ5.2.6\MongoDb\logs\MongoDB.log
Creating service MongoDB.
Service creation successful.
Service can be started from the command line via 'net start "MongoDB"'.
www.2cto.com
强调
1:log一定要指定一个xxx.log文件(文件不存在也要这么写,会自动创建,写成这样是不可以的--logpath d:\mongodb\logs)
2:serviceName的N字母要大写
注意:这条命令要到MongoDB的bin目录下运行,刚开始的时候,我就直接在D:\下运行,结果服务的可执行目录为【"D:\mongod" --logpath "D:\MongoDB\logs\MongoDB.log" --logappend --dbpath "D:\MongoDB\data" --directoryperdb --service 】,肯定是不对的。
该命令行指定了日志文件:E:\APMServ5.2.6\MongoDb\logs\MongoDB.log,日志是以追加的方式输出的;
数据文件目录:E:\APMServ5.2.6\MongoDb\data,并且参数--directoryperdb说明每个DB都会新建一个目录;

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

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Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

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MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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