备份归档日志--查看第一个归档位置过去一天以来生成的归档日志,dest_id代表归档日志存放位置,对应到v$archive_dest中1~10的des
备份归档日志
--查看第一个归档位置过去一天以来生成的归档日志,dest_id代表归档日志存放位置,对应到v$archive_dest中1~10的destination字段值,0代表不可用
SQL> select name from v$archived_log where dest_id=1 and first_time>=sysdate-1;NAME
------------------------------------------------------------------------------------------------------------------------
/Oracle/10g/oracle/log/archive_log/archive_1_23_757801926.arclog
/oracle/10g/oracle/log/archive_log/archive_1_24_757801926.arclog
SQL> select name from v$archived_log where dest_id=10 and first_time>=sysdate-1;
NAME
------------------------------------------------------------------------------------------------------------------------
/oracle/10g/oracle/product/10.2.0/db_1/flash_recovery_area/ORALIFE/archivelog/2011_08_01/o1_mf_1_23_73fljh3f_.arc
/oracle/10g/oracle/product/10.2.0/db_1/flash_recovery_area/ORALIFE/archivelog/2011_08_02/o1_mf_1_24_73hwlry6_.arc
SQL> select destination from v$archive_dest;
DESTINATION
------------------------------------------------------------------------------------------------------------------------
/oracle/10g/oracle/log/archive_log
/oracle/10g/oracle/log/archive_log2
USE_DB_RECOVERY_FILE_DEST
10 rows selected.
--拷贝归档日志到指定的备份目录
cp
备份参数文件
1)如果使用文本参数文件(pfile),使用OS命令拷贝到备份目录
2)如果使用spfile,使用create pfile 进行备份
3)如果使用pfile,使用create spfile进行备份
SQL> show parameter spfile
NAME TYPE VALUE
------------------------------------ ----------- ------------------------------
spfile string /oracle/10g/oracle/product/10.
2.0/db_1/dbs/spfileoralife.ora
--创建pfile,相当于备份spfile为pfile
SQL> create pfile = '/oracle/10g/oracle/bakup/database/pfileoralife.ora'
2 from spfile;
File created.
SQL> shutdown immediate
Database closed.
Database dismounted.
ORACLE instance shut down.
--使用pfile启动数据库到nomount状态,,也可以直接startup pfile='pfile全路径名'
SQL> startup nomount pfile='/oracle/10g/oracle/bakup/database/pfileoralife.ora';
ORACLE instance started.
Total System Global Area 528482304 bytes
Fixed Size 1220360 bytes
Variable Size 146800888 bytes
Database Buffers 373293056 bytes
Redo Buffers 7168000 bytes
SQL> show parameter pfile;--当用pfile启动数据库时,spfile参数为空
NAME TYPE VALUE
------------------------------------ ---------------------- ------------------------------
spfile string
SQL> show parameter spfile;
NAME TYPE VALUE
------------------------------------ ---------------------- ------------------------------
spfile string
SQL> alter database mount;
Database altered.
SQL> alter database open;
Database altered.
SQL> shutdown immediate
Database closed.
Database dismounted.
ORACLE instance shut down.

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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