What are the ways to optimize MySQL?

How to Optimize MySQL Database

1. Understand Your Workload.
2. Optimize Queries.
3. Don’t Use MySQL as a Queue.
4. Monitor the Fundamental Resources.
5. Filter Results.
6. Optimize Subqueries.
7. Recognize Scalability Problems.
8. Query the Cache.

How do you optimize a database performance?

Tips to Increase Database Performance

1. Tip 1: Optimize Queries.
2. Tip 2: Improve Indexes.
3. Tip 3: Defragment Data.
4. Tip 4: Increase Memory.
5. Tip 5: Strengthen CPU.
6. Tip 6: Review Access.
7. SolarWinds Database Performance Analyzer (DPA)
8. SolarWinds Database Performance Monitor (DPM)

What is database optimization in MySQL?

Fortunately, many MySQL performance problems can be rectified by implementing MySQL optimize DB best practices. Database optimization can help you identify bottlenecks, eliminate the guesswork associated with tuning queries, and target insufficient processes.

How do I monitor MySQL performance?

MySQL users have a number of options for monitoring query latency, both by making use of MySQL’s built-in metrics and by querying the performance schema. Enabled by default since MySQL 5.6. 6, the tables of the performance_schema database within MySQL store low-level statistics about server events and query execution.

When should I use optimize in MySQL?

You can use OPTIMIZE TABLE to reclaim the unused space and to defragment the data file. After extensive changes to a table, this statement may also improve performance of statements that use the table, sometimes significantly.

What should I monitor in MySQL?

Here are the top 10 things to monitor on your MySQL.

• MySQL availability. Yes, this is the first thing you should be looking at!
• Presence of insecure users and databases. Do any of your MySQL users have ‘\%’ as host?
• Aborted connects.
• Error log.
• InnoDB Deadlocks.
• Change in server configuration.
• Slow Query log.
• Slave lag.

What is MySQL performance metrics?

Measuring MySQL database performance Workload metrics measure the overall performance of a database by gauging the amount of work or output it can produce in a given period. Resource metrics, meanwhile, measure how much hardware, software, and network resources a database consumes to function.