当我们不小心误操作致使数据库数据丢失、改变时, 需要对数据库对象做基于时间点的恢复,找到我们需要的数据,这个时间点不能认为精确确定,我们可以通过对oracle日志进行分析,而获得无操作的精确时间点。 oracle db提供了一个分析日志包logmnr logminer 工
当我们不小心误操作致使数据库数据丢失、改变时, 需要对数据库对象做基于时间点的恢复,找到我们需要的数据,这个时间点不能认为精确确定,我们可以通过对oracle日志进行分析,而获得无操作的精确时间点。
oracle db提供了一个分析日志包logmnr
logminer 工具的使用
-------对redo log 进行挖掘,找出在某个时间点所作的DDL 或DML 操作(包括:时间点、datablock scn 、sql语句)
实验测试
SQL> select name from v$archived_log; NAME -------------------------------------------------- /oracle/arch1/1_2_883536782.dbf SQL> SQL> SQL> delete from scott.t1; 576 rows deleted. SQL> alter system archive log current; System altered. SQL> create table scott.t6 as select * from scott.emp; Table created. SQL> alter system archive log current; System altered. SQL> select name from v$archived_log; NAME -------------------------------------------------- /oracle/arch1/1_2_883536782.dbf /oracle/arch1/1_3_883536782.dbf /oracle/arch1/1_4_883536782.dbf
--启动log miner添加要分析的日志
SQL> execute dbms_logmnr.add_logfile(logfilename=>'/oracle/arch1/1_2_883536782.dbf',options=>dbms_logmnr.new); PL/SQL procedure successfully completed.
--添加需要分析的日志
SQL> execute dbms_logmnr.add_logfile(logfilename=>'/oracle/arch1/1_3_883536782.dbf',options=>dbms_logmnr.addfile); PL/SQL procedure successfully completed. SQL> execute dbms_logmnr.add_logfile(logfilename=>'/oracle/arch1/1_4_883536782.dbf',options=>dbms_logmnr.addfile) PL/SQL procedure successfully completed.
--执行log miner
SQL> execute dbms_logmnr.start_logmnr(options=>dbms_logmnr.dict_from_online_catalog); PL/SQL procedure successfully completed.
--查询分析结果
SQL> alter session set nls_date_format='yyyy-mm-dd hh24:mi:ss'; Session altered. SQL> select username,scn,timestamp,sql_redo from v$logmnr_contents where seg_name='T1'; USERNAME SCN TIMESTAMP ------------------------------ ---------- ------------------- SQL_REDO -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- delete from "SCOTT"."T1" where "EMPNO" = '7782' and "ENAME" = 'CLARK' and "JOB" = 'MANAGER' and "MGR" = '7839' and "HIREDATE" = TO_DATE('1981-06-09 00:00:00', 'yyyy-mm-dd hh24:mi:ss') and "SAL" = '245 0' and "COMM" IS NULL and "DEPTNO" = '10' and ROWID = 'AAAVbSAAFAAAACXABi'; SYS 1494545 2015-06-28 04:24:44 delete from "SCOTT"."T1" where "EMPNO" = '7839' and "ENAME" = 'KING' and "JOB" = 'PRESIDENT' and "MGR" IS NULL and "HIREDATE" = TO_DATE('1981-11-17 00:00:00', 'yyyy-mm-dd hh24:mi:ss') and "SAL" = '500 0' and "COMM" IS NULL and "DEPTNO" = '10' and ROWID = 'AAAVbSAAFAAAACXABj'; SYS 1494545 2015-06-28 04:24:44 delete from "SCOTT"."T1" where "EMPNO" = '7844' and "ENAME" = 'TURNER' and "JOB" = 'SALESMAN' and "MGR" = '7698' and "HIREDATE" = TO_DATE('1981-09-08 00:00:00', 'yyyy-mm-dd hh24:mi:ss') and "SAL" = '1 。。。。。
--结束log miner 分析
SQL> execute dbms_logmnr.end_logmnr; PL/SQL procedure successfully completed.

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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