MySQL is a widely used relational database management system. Due to its high performance, scalability and open source nature, it has become the first choice for many enterprises and individuals. However, as the amount of data continues to increase and the complexity of the data continues to increase, MySQL's performance problems begin to emerge.

One of the important performance issues is query time. Query time refers to the time it takes for a MySQL query. The shorter the query time, the higher the performance of MySQL and the ability to handle more query requests. To address this problem, we can improve MySQL performance through query time analyzer.

What is Query Time Analyzer?
Query time analyzer is a performance analysis tool provided by MySQL, which can help users analyze the execution time of SQL query statements, find queries with long execution times, and then optimize the corresponding queries. The query time analyzer mainly provides two analysis methods:

1. Explain method: When executing this method, MySQL will simulate the execution of the query statement and output the relevant execution plan, including the tables, indexes, and Number of scanned lines, sorting method, etc. According to the execution plan, the execution efficiency of the SQL query statement can be judged and possible problems can be found, such as too many table scans, lack of indexes, etc.
2. Profiling method: When executing this method, MySQL will record the execution process of the SQL query statement in detail, including execution time, number of scanned rows, sorting method, index usage, etc. Users can find out the performance bottlenecks based on the recorded data and optimize the corresponding queries.

How to use Query Time Analyzer to improve MySQL performance?
The following is a description of how to use the query time analyzer to improve MySQL performance for the two query time analyzer methods.

1. Explain method
   (1) Use Explain to analyze the execution plan of the SQL query statement
   In MySQL, you can use the Explain keyword to query the execution plan of the SQL query statement. Specifically The format is as follows:

Explain select * from table where id=1;

Executing the above command will output the execution plan of the current query, for example:

Among them, id represents the sequence number of each operation in the execution plan; select_type represents the type of the current operation; table represents the table name of the operation; type represents the index type used by the operation; possible_keys represents the index that may be used; key represents the final The selected index; key_len represents the length of the index; ref represents the columns used in the index; rows represents the estimated number of rows in the query results; filtered represents the filtered proportion of the query results; Extra represents other related information.

Based on the above output content, you can judge the execution efficiency of SQL query statements and identify possible problems, such as too many table scans, lack of indexes, etc.

(2) Use index optimization statements
The query time analyzer based on the Explain method can also use index optimization statements to optimize the execution plan of SQL query statements. The specific format is as follows:

ALTER TABLE table_name ADD INDEX index_name (columns);

For example:

alter table table add index (id);

After executing this statement, the id field of the table will be Add an index to make the query statement locate records that meet the conditions faster when querying.

2. Profiling method
   (1) Turn on the Profiling function
   You can turn on the Profiling function by setting the parameters of the MYSQL server. The specific operations are as follows:
3. Set the storage method of the Profiling function
   In the MYSQL configuration file, add the following content:

[mysqld]

Enable none It will prompt that it is not turned on when SHOW PROFILES

Only when eva, snapshot or all are enabled can you see the executed SQL statement when SHOW PROFILES

eva: Record SQL information at the end of the request; snapshot: Record SQL information regularly; all: Record SQL information at any time

log: Store SQL logs in the default error log file; file:/usr/local/mysql/var/data/mylog.log: Store the SQL log in the specified file

profiling=eva
profiling_history_size=20

The above code indicates that the eva storage method is enabled and the maximum number of historical records for recording SQL information is 20.

2. Enable Profiling function
   In the MYSQL client, execute the following command to enable the Profiling function:

set profiling = 1;

Or set the timeout:

set profiling = 1; set profiling_history_size=20; set profiling_history_size=1000000;

Under normal circumstances, while executing the SQL statement, the profiling log file will monitor the occupied capacity , once the capacity limit is exceeded, MYSQL will stop recording.

(2) View the Profiling log
After the Profiling process is completed, you can view the Profiling log through the following command:

show profiles;

This command will output all executed Profiling information of SQL statements, including execution time of SQL statements, number of rows scanned, sorting method, index usage, etc. By analyzing this record, you can find out where MySQL's performance bottleneck lies and optimize accordingly.

Summary
Through the query time analyzer, you can comprehensively understand the execution process and performance bottlenecks of MySQL query statements, which helps to optimize SQL query statements and improve the performance of MySQL. In practical applications, it is necessary to tailor the corresponding query time analysis plan based on specific business conditions in order to better exert the effect of the analysis tool.

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