在MySQL 5.1的慢查询日志中,不使用索引的慢查询同使用索引的查询一样记录。要想防止不使用索引的慢查询记入慢查询日志,使用--log
当使用--log-slow-queries[=file_name]选项启动时,mysqld写一个包含所有执行时间超过long_query_time秒的SQL语句的日志文件。获得初使表锁定的时间不算作执行时间。
如果没有给出file_name值, 默认未主机名,后缀为-slow.log。如果给出了文件名,但不是绝对路径名,文件则写入数据目录。
语句执行完并且所有锁释放后记入慢查询日志。记录顺序可以与执行顺序不相同。
慢查询日志可以用来找到执行时间长的查询,可以用于优化。但是,检查又长又慢的查询日志会很困难。要想容易些,你可以使用mysqldumpslow命令获得日志中显示的查询摘要来处理慢查询日志。
在MySQL 5.1的慢查询日志中,不使用索引的慢查询同使用索引的查询一样记录。要想防止不使用索引的慢查询记入慢查询日志,使用--log-short-format选项。
在MySQL 5.1中,通过--log-slow-admin-statements服务器选项,你可以请求将慢管理语句,例如OPTIMIZE TABLE、ANALYZE TABLE和 ALTER TABLE写入慢查询日志。
用查询缓存处理的查询不加到慢查询日志中,因为表有零行或一行而不能从索引中受益的查询也不写入慢查询日志。
mysqldumpslow 的常用参数如下:
-s 后面接下面的参数表示 mysqldumpslow 结果显示的顺序!
c query执行的次数
t sql执行的时间
l lock锁表的时间
r sql返回的行数
ac,at,al,ar,表示倒序排列
-t,是top n,即为返回前面n条数据。
-g,后边可以写一个正则匹配模式,大小写不敏感
显示执行时间最长的前两个
[root@rac3 python]# mysqldumpslow -s t -t 2 /opt/mysql/data/slowquery.log
Reading mysql slow query log from /opt/mysql/data/slowquery.log
Count: 2 Time=412.54s (825s) Lock=0.00s (0s) Rows=1.0 (2), root[root]@localhost
select count(N) from sbtest ,t1 where t1.c=sbtest.c
Count: 1 Time=778.20s (778s) Lock=0.00s (0s) Rows=1.0 (1), root[root]@localhost
select count(N) from sbtest where sbtest.id not in ( select id from t1 )
#显示次数最多的前两个
[root@rac3 python]# mysqldumpslow -s c -t 2 /opt/mysql/data/slowquery.log
Reading mysql slow query log from /opt/mysql/data/slowquery.log
Count: 12 Time=0.00s (0s) Lock=0.00s (0s) Rows=1.0 (12), root[root]@localhost
select count(N) from tab_1
Count: 2 Time=412.54s (825s) Lock=0.00s (0s) Rows=1.0 (2), root[root]@localhost
select count(N) from sbtest ,t1 where t1.c=sbtest.c
[root@rac3 python]#

The main difference between MySQL and SQLite is the design concept and usage scenarios: 1. MySQL is suitable for large applications and enterprise-level solutions, supporting high performance and high concurrency; 2. SQLite is suitable for mobile applications and desktop software, lightweight and easy to embed.

Indexes in MySQL are an ordered structure of one or more columns in a database table, used to speed up data retrieval. 1) Indexes improve query speed by reducing the amount of scanned data. 2) B-Tree index uses a balanced tree structure, which is suitable for range query and sorting. 3) Use CREATEINDEX statements to create indexes, such as CREATEINDEXidx_customer_idONorders(customer_id). 4) Composite indexes can optimize multi-column queries, such as CREATEINDEXidx_customer_orderONorders(customer_id,order_date). 5) Use EXPLAIN to analyze query plans and avoid

Using transactions in MySQL ensures data consistency. 1) Start the transaction through STARTTRANSACTION, and then execute SQL operations and submit it with COMMIT or ROLLBACK. 2) Use SAVEPOINT to set a save point to allow partial rollback. 3) Performance optimization suggestions include shortening transaction time, avoiding large-scale queries and using isolation levels reasonably.

Scenarios where PostgreSQL is chosen instead of MySQL include: 1) complex queries and advanced SQL functions, 2) strict data integrity and ACID compliance, 3) advanced spatial functions are required, and 4) high performance is required when processing large data sets. PostgreSQL performs well in these aspects and is suitable for projects that require complex data processing and high data integrity.

The security of MySQL database can be achieved through the following measures: 1. User permission management: Strictly control access rights through CREATEUSER and GRANT commands. 2. Encrypted transmission: Configure SSL/TLS to ensure data transmission security. 3. Database backup and recovery: Use mysqldump or mysqlpump to regularly backup data. 4. Advanced security policy: Use a firewall to restrict access and enable audit logging operations. 5. Performance optimization and best practices: Take into account both safety and performance through indexing and query optimization and regular maintenance.

How to effectively monitor MySQL performance? Use tools such as mysqladmin, SHOWGLOBALSTATUS, PerconaMonitoring and Management (PMM), and MySQL EnterpriseMonitor. 1. Use mysqladmin to view the number of connections. 2. Use SHOWGLOBALSTATUS to view the query number. 3.PMM provides detailed performance data and graphical interface. 4.MySQLEnterpriseMonitor provides rich monitoring functions and alarm mechanisms.

The difference between MySQL and SQLServer is: 1) MySQL is open source and suitable for web and embedded systems, 2) SQLServer is a commercial product of Microsoft and is suitable for enterprise-level applications. There are significant differences between the two in storage engine, performance optimization and application scenarios. When choosing, you need to consider project size and future scalability.

In enterprise-level application scenarios that require high availability, advanced security and good integration, SQLServer should be chosen instead of MySQL. 1) SQLServer provides enterprise-level features such as high availability and advanced security. 2) It is closely integrated with Microsoft ecosystems such as VisualStudio and PowerBI. 3) SQLServer performs excellent in performance optimization and supports memory-optimized tables and column storage indexes.


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