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Home Operation and Maintenance CentOS How to configure slow query log in centos redis

How to configure slow query log in centos redis

Apr 14, 2025 pm 04:54 PM
redis centos red

Enable Redis slow query logs on CentOS system to improve performance diagnostic efficiency. The following steps will guide you through the configuration:

Step 1: Locate and edit the Redis configuration file

First, find the Redis configuration file, usually located in /etc/redis/redis.conf . Open the configuration file with the following command:

 sudo vi /etc/redis/redis.conf

Step 2: Adjust the slow query log parameters

In the configuration file, find and modify the following parameters:

 <code># 慢查詢閾值(毫秒) slowlog-log-slower-than 10000 # 慢查詢?nèi)罩咀畲髼l目數(shù)slowlog-max-len 128</code>

slowlog-log-slower-than specifies the threshold (milliseconds) for slow query, defaulting to 10000 milliseconds (10 seconds). You can adjust this value according to actual conditions. slowlog-max-len sets the maximum number of entries for slow query logs, the default is 128.

Step 3: Save and restart Redis service

After saving the configuration file ( :wq ), restart the Redis service to make the configuration take effect:

 sudo systemctl restart redis

Step 4: Verify the slow query log (optional)

You can view the current slow query log using the following command:

 sudo redis-cli SLOWLOG GET

This command displays all slow query records.

Step 5: Configure log file output (optional)

If you need to write the slow query log to a specific file, please add the following line to the configuration file, create the log file and set permissions:

 <code>slowlog-log-file /var/log/redis/slow.log</code>

Then execute the following command:

 sudo mkdir -p /var/log/redis
sudo touch /var/log/redis/slow.log
sudo chown redis:redis /var/log/redis/slow.log
sudo systemctl restart redis

The slow query log will be written to /var/log/redis/slow.log .

After completing the above steps, the Redis slow query log configuration on your CentOS system is complete. You can identify and optimize database performance bottlenecks by analyzing logs.

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