从官网上下载sakai-demo-2.6.2,默认采用的是内存数据库hsqldb,想使用mysql。那么hellip;hellip;1、mysql中的表,字段,数据什
从官网上下载sakai-demo-2.6.2,默认采用的是内存数据库hsqldb,,想使用mysql。
那么……
1、mysql中的表,字段,数据什么的是怎么来的?我在官网上找了番,没有发现mysql的备份文件,ddl什么的,只有一些数据库升级文件什么的,难道我装2.6.2需要从1.5开始安装么..囧。
方案一:下载sakai源代码,搜索所有的*.sql文件,找出2.6.2版本的数据库文件(没有升级标记的文件),然后导入数据库。不推荐,这种方式导入的文件可能不全,而且数据库之间有依赖,出错很郁闷,反正我是弄一半放弃了。
方案二:将hsqldb数据库转化为mysql 数据库。这个是最妙的,因为hsqldb中是sakai实时运行中的所有数据,不用担心数据是否齐全的问题;而且有工具MySQL Migration Toolkit可以直接转换,无痛操作…网上有详细的教程+from+HSQLDB+to+MySQL
要提醒的是:Source Database中connection String的值为sakai.properties中某个字段,比如:url@javax.sql.BaseDataSource=jdbc:hsqldb:file:${sakai.home}db/sakai.db,注意不要在.db后面加后缀了,虽然你疑问,sakai.db根本不是具体的文件(是的,他仅仅是一个前缀)
2、设置sakai加载mysql数据库。
注释掉url@javax.sql.BaseDataSource=jdbc:hsqldb:file:${sakai.home}db/sakai.db;hsqldb.default_table_type=cached
添加下面命令即可:
#username@javax.sql.BaseDataSource=sakai
#password@javax.sql.BaseDataSource=!@#$%)(*&
#vendor@org.sakaiproject.db.api.SqlService=mysql
#driverClassName@javax.sql.BaseDataSource=com.mysql.jdbc.Driver
#hibernate.dialect=org.hibernate.dialect.MySQLInnoDBDialect
#url@javax.sql.BaseDataSource=jdbc:mysql://127.0.0.1:3306/sakai?useUnicode=true&characterEncoding=UTF-8
#validationQuery@javax.sql.BaseDataSource=select 1 from DUAL
#defaultTransactionIsolationString@javax.sql.BaseDataSource=TRANSACTION_READ_COMMITTED

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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