这个工具同样来自percona-toolkit
该工具集合的其他工具
MySQL Slave异常关机的处理 (pt-slave-restart)
包括
1.慢日志(默认)
2.tcpdump
3.general log
4.binlog
5.show processlist
实验通过tpcc模拟一定的压力,并开启binlog,general log,slow log和tcpdump收集日志。
1.slow log方式
将slow_query_log设置为on
long_query_time设置为0
重新连接服务器(一般意味着中间件服务器重启)
这样慢日志将记录所有的操作。
通过pt-query-digest分析慢日志文件,生成剖析报告
首先是概要信息,包括一共有54.17k个操作,46个语句,平均每秒1.55k查询,剖析报告覆盖的时间等。

概要还包括类似Top SQL的分析
可以从响应时间查看对服务器性能影响最大的SQL,其中R/Call指的是 平均每次执行的响应时间 ResponseTime/Calls

然后就是每条SQL的详细剖析报告,
pct指的是该项占概要报告中的百分比

2.tcpdump方式
因为慢日志方式需要重新连接,而生产环境重启中间件是非常昂贵的操作。
所以在数据库服务器上抓包分析也是一种不错的选择。
pt-query-digest对于抓包有一定的格式。(-x -nn -q -tttt)
-s:源端口
-c:抓包的数量
tcpdump -s 65535 -x -nn -q -tttt -i any -c 100000 port 3306 > test.dmp
在完成抓包采集之后进行分析
pt-query-digest --limit 10 --type tcpdump test.dmp
limit 10 限制显示排名前10的操作
其他方式生成的信息会有缺失,可能达不到预期的效果。
而processlist方式实验失败,尚不清楚如何使用这种方式剖析性能。

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.

SQL commands in MySQL can be divided into categories such as DDL, DML, DQL, DCL, etc., and are used to create, modify, delete databases and tables, insert, update, delete data, and perform complex query operations. 1. Basic usage includes CREATETABLE creation table, INSERTINTO insert data, and SELECT query data. 2. Advanced usage involves JOIN for table joins, subqueries and GROUPBY for data aggregation. 3. Common errors such as syntax errors, data type mismatch and permission problems can be debugged through syntax checking, data type conversion and permission management. 4. Performance optimization suggestions include using indexes, avoiding full table scanning, optimizing JOIN operations and using transactions to ensure data consistency.

InnoDB achieves atomicity through undolog, consistency and isolation through locking mechanism and MVCC, and persistence through redolog. 1) Atomicity: Use undolog to record the original data to ensure that the transaction can be rolled back. 2) Consistency: Ensure the data consistency through row-level locking and MVCC. 3) Isolation: Supports multiple isolation levels, and REPEATABLEREAD is used by default. 4) Persistence: Use redolog to record modifications to ensure that data is saved for a long time.

MySQL's position in databases and programming is very important. It is an open source relational database management system that is widely used in various application scenarios. 1) MySQL provides efficient data storage, organization and retrieval functions, supporting Web, mobile and enterprise-level systems. 2) It uses a client-server architecture, supports multiple storage engines and index optimization. 3) Basic usages include creating tables and inserting data, and advanced usages involve multi-table JOINs and complex queries. 4) Frequently asked questions such as SQL syntax errors and performance issues can be debugged through the EXPLAIN command and slow query log. 5) Performance optimization methods include rational use of indexes, optimized query and use of caches. Best practices include using transactions and PreparedStatemen

MySQL is suitable for small and large enterprises. 1) Small businesses can use MySQL for basic data management, such as storing customer information. 2) Large enterprises can use MySQL to process massive data and complex business logic to optimize query performance and transaction processing.

InnoDB effectively prevents phantom reading through Next-KeyLocking mechanism. 1) Next-KeyLocking combines row lock and gap lock to lock records and their gaps to prevent new records from being inserted. 2) In practical applications, by optimizing query and adjusting isolation levels, lock competition can be reduced and concurrency performance can be improved.


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