在执行存储过程时,我们可能会遇到权限问题 ● 定义者权限存储过程 ● 调用者权限存储过程 在数据库中创建存储过程时,定义者权限是缺省模式 当指定AUTHID CURRENT_USER关键字后,便是调用者权限存储过程 他俩之间最根本的差异在于role能否在存储过程中生效
在执行存储过程时,我们可能会遇到权限问题
● 定义者权限存储过程
● 调用者权限存储过程
在数据库中创建存储过程时,,定义者权限是缺省模式
当指定AUTHID CURRENT_USER关键字后,便是调用者权限存储过程
他俩之间最根本的差异在于role能否在存储过程中生效
㈠ 定义者权限存储过程问题
定义者权限存储过程role无效,必须要有显式授权
即便是拥有dba role,还是不能访问不同用户的表
sys@EMREP> grant connect,resource to u1 identified by u1; Grant succeeded. sys@EMREP> grant dba to u2 identified by u2; Grant succeeded. sys@EMREP> conn u1/u1 Connected. u1@EMREP> create table t as select * from user_objects; Table created. sys@EMREP> conn u2/u2 Connected. u2@EMREP> create or replace procedure p_test 2 as 3 begin 4 delete from u1.t; 5 commit; 6 end; 7 / Warning: Procedure created with compilation errors. u2@EMREP> show error; Errors for PROCEDURE P_TEST: LINE/COL ERROR -------- ----------------------------------------------------------------- 4/3 PL/SQL: SQL Statement ignored 4/18 PL/SQL: ORA-00942: table or view does not exist u2@EMREP> conn u1/u1 Connected. u1@EMREP> grant all on t to u2; Grant succeeded. u1@EMREP> conn u2/u2 Connected. u2@EMREP> create or replace procedure p_test 2 as 3 begin 4 delete from u1.t; 5 commit; 6 end; 7 / Procedure created.
㈡ 调用者权限存储过程问题
调用者权限存储过程role编译不可见,但运行时可见
用动态SQL避免直接授权,而将权限的检查延后至运行时
u2@EMREP> conn u1/u1 Connected. u1@EMREP> revoke all on t from u2; Revoke succeeded. u1@EMREP> conn u2/u2 Connected. u2@EMREP> create or replace procedure p_test 2 authid current_user 3 as 4 begin 5 delete from u1.t; 6 commit; 7 end; 8 / Warning: Procedure created with compilation errors. u2@EMREP> show error; Errors for PROCEDURE P_TEST: LINE/COL ERROR -------- ----------------------------------------------------------------- 5/3 PL/SQL: SQL Statement ignored 5/18 PL/SQL: ORA-00942: table or view does not exist u2@EMREP> create or replace procedure p_test 2 authid current_user 3 as 4 begin 5 execute immediate 6 'delete from u1.t'; 7 commit; 8 end; 9 / Procedure created. u2@EMREP> exec p_test; PL/SQL procedure successfully completed. u2@EMREP> select count(*) from u1.t; COUNT(*) ---------- 0

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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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