Explaining the MySQL Slow Query Log – How to Read and Interpret Slow Query Log?

The MySQL Slow Query Log is a feature that logs SQL statements that exceed a certain threshold of execution time. This log can be used to identify slow queries and to optimize their performance. Here are the steps to read and interpret the MySQL Slow Query Log:

  1. Enable the slow query log: Before you can read the slow query log, you must first enable it. To enable the slow query log, you can add the following lines to the MySQL configuration file (my.cnf or my.ini):

This will enable the slow query log, specify the file location, and set the threshold for a slow query to 1 second.

  1. Analyze the slow query log: Once the slow query log is enabled, you can analyze it to identify slow queries. The log file will contain entries in the following format:

Each entry includes the time the query was executed, the user who executed the query, the execution time of the query, and the number of rows sent and examined.

  1. Interpret the slow query log: To interpret the slow query log, you can focus on the following elements:
    • Query_time: This is the execution time of the query in seconds.
    • Lock_time: This is the time the query spent waiting for locks.
    • Rows_sent: This is the number of rows returned by the query.
    • Rows_examined: This is the number of rows examined by the query.

You should focus on queries with a high Query_time and/or a high Rows_examined value, as these are likely to be the slowest queries. You can then optimize these queries to improve their performance.

  1. Optimize slow queries: To optimize slow queries, you can use the MySQL Explain Plan to analyze the execution plan of the query and identify ways to improve it. You can also use indexes to improve query performance, rewrite the query to use more efficient syntax, or adjust the configuration of MySQL to optimize performance.


In summary, the MySQL Slow Query Log is a valuable tool for identifying slow queries and optimizing their performance. By enabling and analyzing the log, you can gain insights into the performance of your database and take steps to improve it.

About Shiv Iyer 452 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.