ORACLE的数据字典是的重要组成部分之一,它随着数据库的产生而产生, 随着数据库的变化而变化,
体现为sys用户下的一些表和视图。数据字典名称是大写的英文字符。
数据字典里存有用户信息、用户的权限信息、所有数据对象信息、表的约束条件、统计分析数据库的视图等。
我们不能手工修改数据字典里的信息。
很多时候,一般的ORACLE用户不知道如何有效地利用它。
dictionary 全部数据字典表的名称和解释,它有一个同义词dict
dict_column 全部数据字典表里字段名称和解释
如果我们想查询跟索引有关的数据字典时,可以用下面这条SQL语句:
SQL>select * from dictionary where instr(comments,'index')>0;
如果我们想知道user_indexes表各字段名称的详细含义,可以用下面这条SQL语句:
SQL>select column_name,comments from dict_columns where table_name='USER_INDEXES';
依此类推,就可以轻松知道数据字典的详细名称和解释,不用查看ORACLE的其它文档资料了。
下面按类别列出一些ORACLE用户常用数据字典的查询使用方法。
一、用户
查看当前用户的缺省表空间
SQL>select username,default_tablespace from user_users;
查看当前用户的角色
SQL>select * from user_role_privs;
查看当前用户的系统权限和表级权限
SQL>select * from user_sys_privs;
SQL>select * from user_tab_privs;
二、表
查看用户下所有的表
SQL>select * from user_tables;
查看名称包含log字符的表
SQL>select object_name,object_id from user_objects
where instr(object_name,'LOG')>0;
查看某表的创建时间
SQL>select object_name,created from user_objects where object_name=upper('&table_name');
查看某表的大小
SQL>select sum(bytes)/(1024*1024) as "size(M)" from user_segments
where segment_name=upper('&table_name');
查看放在ORACLE的内存区里的表
SQL>select table_name,cache from user_tables where instr(cache,'Y')>0;
三、索引
查看索引个数和类别
SQL>select index_name,index_type,table_name from user_indexes order by table_name;
查看索引被索引的字段
SQL>select * from user_ind_columns where index_name=upper('&index_name');
查看索引的大小
SQL>select sum(bytes)/(1024*1024) as "size(M)" from user_segments
where segment_name=upper('&index_name');
四、序列号
查看序列号,last_number是当前值
SQL>select * from user_sequences;
五、视图
查看视图的名称
SQL>select view_name from user_views;
查看创建视图的select语句
SQL>set view_name,text_length from user_views;
SQL>set long 2000; 说明:可以根据视图的text_length值设定set long 的大小
SQL>select text from user_views where view_name=upper('&view_name');
六、同义词
查看同义词的名称

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.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

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

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

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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