MySQL Not Using All CPU Cores – Optimize MYSQL In 2023

MySQL is used for a lot of different things, from building websites to storing data. But there are times when MySQL may only fully use some of the available CPU cores, which can slow things down. 

MySQL’s single-threaded query execution limits the use of CPU cores. Run multiple queries at once or look into parallel processing tools like Apache Spark to get the most out of your database.

In this post, we’ll look into why MySQL doesn’t use all of its CPU cores well and look at some possible ways to fix this problem.

MySQL Not Using All CPU Cores
Source : DBA Stack Exchange

The Myth Of CPU Multi-Core Utilization In MySQL:

1. MySQL’s Single-Threaded Nature:

People often think that MySQL can take advantage of all the features of multi-core CPUs. In fact, MySQL is mostly made to run queries that only use one thread. This means that even on a CPU with more than one core, a single core will handle each query.

2. Concurrency vs. Parallelism:

In MySQL, it’s important to know the difference between concurrency and parallelism:

  • Concurrency: MySQL can handle multiple searches at the same time. This means that multiple clients can send queries to the server at the same time, and MySQL will handle and run these queries effectively.
  • Parallelism: In parallelism, a single query or action is broken up into several smaller tasks that can be run at the same time on different CPU cores. MySQL’s core query work is usually done in a single thread, so a single query can’t use all of the available CPU cores.

Factors Of MySQL Not Utilizing All CPU Cores:

MySQL should be able to use all the CPU cores effectively to get the most out of them, especially when there are a lot of queries or complex jobs to do with the data. But MySQL might not use all of the CPU cores well for a number of reasons:

Factors Of MySQL Not Utilizing All CPU Cores
Source : DBA Stack Exchange

1. Single-Threaded Processes:

Some tasks in MySQL, like query analysis and optimization, can only be done by one thread at a time. This means that even if the CPU has more than one core, these operations will only run on one core, which limits how much the CPU can be used in total.

A number of things cause MySQL’s single-threaded query performance:

  • InnoDB, which is MySQL’s default storage engine, uses a single thread to handle searches. Even on multi-core platforms, complex queries like joins and aggregations are usually run one at a time. 
  • The processing plan for a query is made by MySQL’s query optimizer, which is a single-threaded program. Optimizer jobs, like rewriting queries and figuring out costs, are done one after the other.
  • The locking and separation features of InnoDB can make it harder to work in parallel. Even though multiple transactions can run at the same time, they may compete for locks, which slows down processing. 
  • Some storage engines may have built-in limits that make it impossible to run queries in parallel. In some cases, custom storage engines or engines from a third party may offer better symmetry.

2. Thread Contentions:

In MySQL, different threads do things like run queries, handle connections, and change data. If these threads try to use the same resources, it can cause the CPU cores to be used inefficiently.

3. Configuration And Tuning:

The configuration choices of MySQL have a big impact on how well it works. If MySQL isn’t set up right, queries and jobs might not be spread out evenly across CPU cores, which can lead to underutilization.

4. Inefficient Queries: 

 If SQL searches aren’t optimized well, MySQL may only use some CPU cores well. Complex queries or ones that aren’t indexed correctly can cause slowdown and uneven use of the CPU cores.

How To Improve CPU Core Utilization In MySQL? Optimize MySQL Performance:

Even though MySQL’s core query execution is still single-threaded, there are ways to use multi-core computers more effectively:

How To Improve CPU Core Utilization In MySQL? Optimize MySQL Performance:
Source : Dynimize

1. Concurrent Query Execution:

Run more than one query at the same time to use more than one CPU core. Use connection pooling to handle client connections and the execution of queries in an effective way.

2. Batch Processing:

Break up big jobs into smaller groups that can be done at the same time. INSERT, UPDATE, or DELETE statements in batches to make the most of computers with more than one core.

3. Parallel Processing Frameworks:

For analytics and data processing jobs, you should use frameworks like Apache Spark or Presto. These tools are made for parallelism and can spread work across multiple cores and nodes.

4. Database Replication:

Set up read replicas to help the main database handle more read queries. Spread read queries across copies to improve how many queries can be done at the same time.

5. In-Memory Storage Engines:

Look into storage engines like TokuDB or MemSQL, which may offer better support for parallel query processing for certain workloads.

6. Upgrade Hardware:

If your MySQL workload is always CPU-bound and you have already optimized your queries and configuration settings, consider upgrading your hardware to a machine with more CPU cores. This gives MySQL more space to divide up tasks.

7. Optimize Configuration:

Check your MySQL configuration values and make any necessary changes. Look at values like the number of worker threads, the size of the query cache, and the size of the InnoDB buffer pool. When these settings are set up correctly, they can help MySQL do its job more quickly.

8. Use Connection Pooling:

Use a remote connection pooler like ProxySQL or a connection pooling system like MySQL’s Connection Pooling. This can help MySQL control and improve how it handles client connections, reducing bottlenecks and making better use of CPU cores.

9. Indexing And Query Optimization:

Look at your database queries to find ones that need to be revised or take too long. Make sure your tables are properly indexed and that your queries are made in an optimized way to reduce CPU load.

10. Partitioning And Sharding:

If your information is very big, think about splitting it up or splitting it into pieces. This breaks the data into smaller, easier-to-handle pieces, which makes it easier for MySQL to send searches to different CPU cores. Use table splitting to break up big tables into smaller, easier-to-handle parts.

Frequently Asked Questions:

1. Why Does MySQL Eat All Memory?

If your MySQL instance has a lot of tables that are linked by foreign keys, the InnoDB data dictionary cache may use several GBs of memory. It is often forgotten when setting up MySQL buffers and caches, and it could be one reason for unexpectedly high memory usage or out-of-memory (OOM) problems.

2. How To Reduce CPU Usage In MySQL?

Using Performance Insights, you can find out which queries are running on the instance and causing it to use a lot of CPU. First, turn on MySQL Performance Insights. Then, you can use Performance Insights to make your task as efficient as possible. Make sure you talk to your DBA.

3. Can I Make MySQL Use All CPU Cores For A Single Query?

No, MySQL’s query performance is mostly single-threaded, which means that a single query can only use one CPU core at a time. To take advantage of multiple cores, run various queries at the same time.

4. How Many Cores Does MySQL Use?

MySQL usually only uses one CPU core per query, even when a GROUP BY query is being run. Run multiple queries at the same time or use a parallel processing tool like Apache Spark to take advantage of more than one CPU core. Because MySQL can only run one task at a time, it can’t use all of the CPU cores for a single query.

5. How To Check CPU And Memory Utilization In MySQL?

Use the MySQL Performance Schema or performance tracking tools like “top” or “htop” on the server running MySQL to see how much CPU is being used. To keep track of how much memory MySQL is using, look at its performance schema or use the “SHOW GLOBAL STATUS” command and look at values like “innodb_buffer_pool_size” and “key_buffer_size.”


MySQL can only run queries on a single thread at a time. This is a known limitation, but you can still use multi-core computers effectively. By using techniques like concurrent query execution, batch processing, and tools for parallel processing, you can spread out the work and make the system run better overall.

MySQL might not use all of the CPU cores for a single query, but it can handle multiple queries at the same time. This makes it a good choice for many apps if it is used wisely. Keep up with the latest changes and improvements to MySQL to get the most out of your multi-core gear.