MySQL凭借着出色的性能、低廉的成本、丰富的资源,已经成为绝大多数互联网公司的首选关系型数据库。虽然性能出色,但所谓“好马配好鞍”,如何能够更好的使用它,已经成为开发工程师的必修课,我们经常会从职位描述上看到诸如“精通MySQL”、“SQL语句优化”、“了解数据库原理”等要求。我们知道一般的应用系统,读写比例在10:1左右,而且插入操作和一般的更新操作很少出现性能问题,遇到最多的,也是最容易出问题的,还是一些复杂的查询操作,所以查询语句的优化显然是重中之重。
问题:cpu负载过高,达到36。
现象:通过mysqladmin -uroot -p processlist 查看到大量如下信息:
Sending data select * from `rep_corp_vehicle_online_count` where corp_id = 48 and vehicle_id = 10017543
根据以上的可能是表rep_corp_vehicle_online_count的问题 做出如下测试:
查看表结构:
mysql> desc rep_corp_vehicle_online_count; +-------------+-------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-------------+-------------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | corp_id | int(11) | NO | | NULL | | | vehicle_id | int(11) | NO | | NULL | | | online_day | varchar(20) | NO | | NULL | | | loc_total | int(11) | NO | | NULL | | | create_time | datetime | NO | | NULL | | | update_time | datetime | NO | | NULL | | +-------------+-------------+------+-----+---------+----------------+ 7 rows in set (0.00 sec)
查看索引,只有主键索引:
mysql> show index from rep_corp_vehicle_online_count; +-------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | +-------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | rep_corp_vehicle_online_count | 0 | PRIMARY | 1 | id | A | 1247259 | NULL | NULL | | BTREE | | | +-------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ 1 row in set (0.00 sec)
代码执行情况:
mysql>explain select * from rep_corp_vehicle_online_count where corp_id = 79 and vehicle_id = 10016911 and online_day = '2016-03-29'\G *************************** 1. row *************************** id: 1 select_type: SIMPLE table: rep_corp_vehicle_online_count type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 1248495 Extra: Using where 1 row in set (0.00 sec)
表数据分析情况,重复数据很多:
mysql> select count(distinct corp_id) from rep_corp_vehicle_online_count; +-------------------------+ | count(distinct corp_id) | +-------------------------+ | 18 | +-------------------------+ 1 row in set (0.63 sec) mysql> select count(corp_id) from rep_corp_vehicle_online_count; +----------------+ | count(corp_id) | +----------------+ | 1239573 | +----------------+ 1 row in set (0.00 sec) mysql> select count(distinct vehicle_id) from rep_corp_vehicle_online_count; +----------------------------+ | count(distinct vehicle_id) | +----------------------------+ | 2580 | +----------------------------+ 1 row in set (1.03 sec) mysql>explain select count(vehicle_id) from rep_corp_vehicle_online_count; +-------------------+ | count(vehicle_id) | +-------------------+ | 1239911 | +-------------------+ 1 row in set (0.00 sec)
最后处理,创建索引:
mysql> create index r_c_v on rep_corp_vehicle_online_count(corp_id,vehicle_id); Query OK, 1487993 rows affected (6.09 sec) Records: 1487993 Duplicates: 0 Warnings: 0 mysql> show index from rep_corp_vehicle_online_count; +-------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | +-------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | rep_corp_vehicle_online_count | 0 | PRIMARY | 1 | id | A | 1490176 | NULL | NULL | | BTREE | | | | rep_corp_vehicle_online_count | 1 | r_c_v | 1 | corp_id | A | 18 | NULL | NULL | | BTREE | | | | rep_corp_vehicle_online_count | 1 | r_c_v | 2 | vehicle_id | A | 2596 | NULL | NULL | | BTREE | | | +-------------------------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ 3 rows in set (0.00 sec)
添加索引过后负载降低到了1.73:
以上内容是小编给大家介绍的Mysql数据库之索引优化 ,更多相关内容请关注PHP中文网(www.php.cn)!

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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