生成 Active Session History (ASH) 报告 ASH 报告的作用: 利用 ASH 报告可以分析持续时间通常只有几分钟的瞬间性能问题 根据各种维度(如 time、session、module、action 或 sql_id )或这些维度的组合进行确定范围或目标的性能分析 瞬间性能问题持续的时间
生成 Active Session History (ASH) 报告ASH 报告的作用:
利用 ASH 报告可以分析持续时间通常只有几分钟的瞬间性能问题
根据各种维度(如 time、session、module、action 或 sql_id )或这些维度的组合进行确定范围或目标的性能分析
瞬间性能问题持续的时间非常短,不会出现在Automatic Database Diagnostics Monitor (ADDM) 分析中。ADDM 尝
试在分析期间根据问题读 DB time 的影响报告重大的性能问题。如果某个特定的问题持续的时间非常短暂,则该问题
的严重性可能就被均匀化,或因分析期间产生的其他性能问题而减小。因此,在 ADDM 中可能找不到该问题的记录。
ADDM 是否捕获某个性能问题,取决于该问题的持续时间与 AWR 快照之间的间隔的时间比。
如果性能问题持续的时间与快照间隔比非常大,则 ADDM 将捕获该问题。例如,如果快照间隔设为 1 小时,而性能问
题持续了 30 分钟,则该问题就不会被视为瞬间性能问题,因为其持续时间与快照间隔比较大,很可能被 ADDM 捕获
到。
如果某个性能问题只持续 2 分钟,该问题可能就是一个短暂的性能问题,因为其持续时间与快照间隔的比例非常小,
不会出现在 ADDM 发现的问题当中。比如,如果用户通知您系统在晚上 10 点到 10 点过 10 分之间非常慢,而 ADDM 分析
的时段在晚上 10 点到 11 点之间,并且未显示任何性能问题,则可能发生了短暂的性能问题,在用户所报告的10分钟
时段内只持续了数分钟。
下面将介绍如何生成 ASH 报告:
1.生成单实例 ASH 报告
@$ORACLE_HOME/rdbms/admin/ashrpt.sql
2.生成 Oracle RAC 环境下特定数据库实例的 ASH 报告
@$ORACLE_HOME/rdbms/admin/ashrpti.sql
3.生成 Oracle RAC ASH 报告
@$ORACLE_HOME/rdbms/admin/ashrpti.sql
http://blog.csdn.net/xiangsir/article/details/8666171

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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