转载:http://blog.163.com/ji_1006/blog/static/106123412013101421530142/
运行中的mysql状态查看
对正在运行的mysql进行监控,其中一个方式就是查看mysql运行状态。
(1)QPS(每秒Query量)
QPS = Questions(or Queries) / seconds
mysql > show global status like 'Question%';
(2)TPS(每秒事务量)
TPS = (Com_commit + Com_rollback) / seconds
mysql > show global status like 'Com_commit';
mysql > show global status like 'Com_rollback';
(3)key Buffer 命中率
mysql>show global status like 'key%';
key_buffer_read_hits = (1-key_reads / key_read_requests) * 100%
key_buffer_write_hits = (1-key_writes / key_write_requests) * 100%
(4)InnoDB Buffer命中率
mysql> show status like 'innodb_buffer_pool_read%';
innodb_buffer_read_hits = (1 - innodb_buffer_pool_reads / innodb_buffer_pool_read_requests) * 100%
(5)Query Cache命中率
mysql> show status like 'Qcache%';
Query_cache_hits = (Qcahce_hits / (Qcache_hits + Qcache_inserts )) * 100%;
(6)Table Cache状态量
mysql> show global status like 'open%';
比较 open_tables 与 opend_tables 值
(7)Thread Cache 命中率
mysql> show global status like 'Thread%';
mysql> show global status like 'Connections';
Thread_cache_hits = (1 - Threads_created / connections ) * 100%
(8)锁定状态
mysql> show global status like '%lock%';
Table_locks_waited/Table_locks_immediate=0.3% 如果这个比值比较大的话,说明表锁造成的阻塞比较严重
Innodb_row_lock_waits innodb行锁,太大可能是间隙锁造成的
(9)复制延时量
mysql > show slave status
查看延时时间
(10) Tmp Table 状况(临时表状况)
mysql > show status like 'Create_tmp%';
Created_tmp_disk_tables/Created_tmp_tables比值最好不要超过10%,如果Created_tmp_tables值比较大,
可能是排序句子过多或者是连接句子不够优化
(11) Binlog Cache 使用状况
mysql > show status like 'Binlog_cache%';
如果Binlog_cache_disk_use值不为0 ,可能需要调大 binlog_cache_size大小
(12) Innodb_log_waits 量
mysql > show status like 'innodb_log_waits';
Innodb_log_waits值不等于0的话,表明 innodb log buffer 因为空间不足而等待
比如命令:
>#show global status;
虽然可以使用:
>#show global status like %...%;
来过滤,但是对应长长的list,每一项都代表什么意思,还是有必要弄清楚。

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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