CROSSCHECK命令用户核对备份文件,以确保RMAN资料库与备份文件保持同步。当执行该命令时,如果RMAN资料库记录的状态与实际备份文
在用DELETE OBSOLETE 命令删除废弃的备份文件,如果出现如下错误(RMAN-06207 & RMAN-06208),那么需要用CROSSCHECK命令来解决:
RMAN-06207: WARNING: 2 objects could not be deleted for DISK channel(s) due
RMAN-06208: to mismatched status. Use CROSSCHECK command to fix status
CROSSCHECK命令用户核对备份文件,以确保RMAN资料库与备份文件保持同步。当执行该命令时,如果RMAN资料库记录的状态与实际备份文件不匹配,则会更新资料库里的状态使其与实际备份文件状态一致;若备份文件处于expired状态,,那么说明该备份已失效,可以删除之;
常用命令介绍:
1.CROSSCHECK BACKUP
用于核对数据库、表空间、数据文件、控制文件、归档日志、SPFILE的备份集。
CROSSCHECK BACKUP ; --核对所有备份(包括有效和失效的备份)
CROSSCHECK BACKUP of database; --核对除控制文件、归档文件外的备份文件
CROSSCHECK BACKUP of tablespace system;
CROSSCHECK BACKUP of datafile 1;
CROSSCHECK BACKUP of controlfile;
CROSSCHECK BACKUP of archivelog all;
CROSSCHECK BACKUP of archivelog sequence 3;
CROSSCHECK BACKUP of spfile;
2.CROSSCHECK BACKUPPIECE
用于 核对特定备份片,该命令需要制定备份片的BP值或备份片名称;
CROSSCHECK BACKUPPIECE 24;
CROSSCHECK BACKUPPIECE '/u01/app/Oracle/rman_backup/OCPYJG_28';
3.CROSSCHECK BACKUPSET
用于核对特定的备份集,该命令需要制定备份集的BP值;
CROSSCHECK BACKUPSET 24;
4.CROSSCHECK COPY
用于核对数据库、表空间、数据文件、控制文件、归档文件的映像副本(即备份是用COPY DATAFILE ...... 或BACKUP AS COPY ......DATAFILE......命令备份数据文件的映像)
CROSSCHECK COPY;
CROSSCHECK COPY of database;
CROSSCHECK COPY of tablespace system;
CROSSCHECK COPY of datafile 1;
CROSSCHECK COPY of controlfile;
CROSSCHECK COPY of archivelog all;
CROSSCHECK COPY of archivelog from sequence 24 until sequence 32;
5.CROSSCHECK DTAFILECOPY
用于核对特定的数据文件映像副本,该命令需要指定映像副本的文件名或KEY值;
CROSSCHECK DATAFILECOPY 2;
CROSSCHECK DATAFILECOPY '/u01/app/oracle/rman_backup/tp9.dbf';
6.CROSSCHECK CONTROLFILECOPY
用于核对特定的控制文件映像副本,该命令需要指定控制文件映像副本的文件名或KEY值;
CROSSCHECK CONTROLFILECOPY 3;
CROSSCHECK CONTROLFILECOPY '/u01/app/oracle/rman_backup/controlfile01.ctl;
7.CROSSCHECK ARCHIVELOG
用于核对特定的归档日志,该命令需要指定归档日志的文件名或KEY值或SEQUENCE值;
CROSSCHECK ARCHIVELOG 36;
CROSSCHECK ARCHIVELOG 'crosscheck archivelog '/u01/app/oracle/product/11g/dbs/arch1_6_813161833.dbf';
CROSSCHECK ARCHIVELOG sequence 7;

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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