运维工程师在一台IBM P750(AIX6.1)上部署了一套oracle(未建库),让我把商用的某库同其做一个DG容灾。我按正常步骤部署了DG。
运维工程师在一台IBM P750(AIX6.1)上部署了一套Oracle(未建库),让我把商用的某库同其做一个DG容灾。我按正常步骤部署了DG。
1.在备库开始日志恢复
alter database recover managed standby database using current logfile disconnect;
2.查看备库是否正常接收日志
select process,client_process,sequence#,status from v$managed_standby;
--正常接收日志
3.查看备库是否正常应用日志
select THREAD#,SEQUENCE#,ARCHIVED,APPLIED,DELETED,STATUS from v$archived_log order by 1,2;
--正常应用日志
但是我在备库的alert日志里发现有如下报错
Mon Mar 24 14:11:14 2014
Process startup failed, error stack:
Errors in file /apps/oracle/diag/rdbms/primary/egap/trace/egap_psp0_18481392.trc:
ORA-27300: OS system dependent operation:fork failed with status: 2
ORA-27301: OS failure message: No such file or directory
ORA-27302: failure occurred at: skgpspawn5
Process PR0S died, see its trace file
后来发现是参数maxuproc不足导致,该参数默认只有128,,该参数决定了每个操作系统用户允许连接的最大进程数,该参数不足时alert日志中会报如上错误。
正常在装rac时这些参数我们都会提前检查,并设为oracle要求的值(要求值为16384),这里可能是运维根本没有检查该参数
检查该参数
lsattr -E -l sys0 -a maxuproc
root@egisbdb1:/#lsattr -E -l sys0 -a maxuproc
maxuproc 128 Maximum number of PROCESSES allowed per user True
修改该参数
chdev -l sys0 -a maxuproc=16384
修改后alert日志中不再报该错误

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


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.

Atom editor mac version download
The most popular open source editor

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

SublimeText3 Linux new version
SublimeText3 Linux latest version

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment
