Though MySQL is considered one of the most popular database managers, it still needs to be optimised every once in a while. On the other hand, when we talk about complex and big data sets, you need to optimise for high performance regularly. MySQL performance tuning basically involves profiling, configuring, and performance monitoring at different levels. The best thing about tuning MySQL is that you don’t need to have a deep understanding or extensive expertise in SQL.
In this blog, we’ll provide you with the best performance tuning tips to ensure your database-driven applications’ reliability, stability, and speed.
In this article, we will take you through the significant performance tuning techniques so that you can ensure the stability, reliability, and speed of your database-driven applications.
Top MySQL Performance Tuning Tips for 2022
1. Balance the Four Main Hardware Resources
To start, you have to evaluate your storage. If you’re still utilising traditional HDD (hard disc drives), you can switch over to SSD (solid-state drives) to enhance performance.
Tools like SAR or iotop from the sysstat package should be utilised to monitor your disk’s input and output rates. If the usage of the disc is greater than other resources, you’ll need to add more storage or upgrade to a faster storage option.
Processors can be defined by the measure of the speed of your system. You can utilise the Linux top command for a breakdown of how your resources are utilized. You need to keep a close look at the MySQL processes and how much processor time they require.
You need to plan ahead. As processors are a bit more expensive to upgrade, However, you may need to invest in maintaining performance if your CPU isn’t operating fast enough.
It is crucial to analyze network traffic to ensure that enough infrastructure is present to manage the load.
If you overload your network, it may lead to server outrages, dropped packets, and latency. Make sure that you have sufficient network bandwidth to facilitate the level of database traffic you receive.
Memory represents the total amount of RAM in your MySQL database storage server. You can adjust the memory cache (more on that later) to improve performance. If you don’t have enough memory or the existing memory isn’t optimized, you can damage your performance instead of improving it.
Like other bottlenecks, if your server is constantly running out of memory, you can upgrade by adding more. If you run short of memory, your server will cache data storage (like a hard drive) to act as memory. Database caching slows down your performance.
2. MySQL Server Configuration
This configuration includes changes to the /etc/mysql/my.cnf file. Be careful and make small changes at once.
query_cache_size – States the size of the cache for MySQL queries waiting to run. It is recommended to start with a smaller value of around 10MB and increase it to 100-200MB or less. Waiting for cache lock queries can occur in a chain if there are too many cached queries. If your queries continue to be backed up, we recommend you use EXPLAIN to evaluate each query and find a more efficient way.
innodb_io_capacity – This variable sets the I/O rate from the storage device. This is directly related to storage drive type and speed. A 5400 rpm HDD has much less capacity than a high-end SSD or Intel Optane. You can adjust this value to match your hardware.
innodb_buffer_pool_size – This setting considers system memory as the database data cache. Increase this value if you have large chunks of data. Note the RAM required to run other system resources.
max_connection – Indicates the number of allowed connections to the database. If you receive the error message “Too many connections,” you may want to increase this value.
3. Use the Latest Version of MySQL
It’s true that utilizing the latest version of MySQL isn’t a good option for order databases. However, whenever possible, you should take a look at which MySQL version is being used and which you should upgrade.
If you are looking for performance enhancement, you may face a challenge if you haven’t upgraded to the newest version of MySQL. However, during ongoing development, it is advised to stick with native MySQL performance enhancement over configuration and scripting files.
4. The EXPLAIN Function is Crucial
Modern MySQL databases include an EXPLAIN function.
A query will be read and evaluated if the EXPLAIN expression is appended to the start of it. EXPLAIN will help you locate any unclear structures or ineffective phrases. The query’s wording can then be changed to prevent unintended table scans or other performance penalties.
5. Use InnoDB, Not MyISAM
MyISAM is a native database style used for some MySQL databases. It is a less efficient database design. The latest InnoDB supports more advanced features and has in-built optimization mechanics.
InnoDB utilizes a clustered index and keeps data in pages. These are stored in continuous physical blocks. If a value is too much for a page, InnoDB relocates it to another location. After that, the value is indexed. It helps maintain relevant data in the exact location at the device of storage. This means it takes the physical hard drive less time to access data.
6. Optimize Queries
A query is a coded order to the database to search for information that matches a specific value. Some query operators require a long time to execute by their sheer nature. Techniques for adjusting SQL performance aid in query optimization for faster execution.
One of the critical challenges of performance tuning is finding queries with slow execution times. Large dataset queries that are frequently used are slow and take up database space. Therefore, the tables cannot be used for any other purposes.
An OLTP database, for instance, needs quick transactions and efficient query processing. Running an ineffective query prevents the database from being used and delays information updates.
Performance may be impacted if your environment uses triggers or other automated queries. Check and terminate MySQL processes add up in time.
Read Also: How to Join Two Tables in MySQL
7. Remember the 3 rules of indexing
Indexing can be considered one of the most confusing topics in databases. There are various ways to get confused about indexes and how servers utilize them. A lot of effort is actually required to understand what’s happening.
A well-designed index serves three viral purposes on a database server.
- With an index, the server can execute the entire query only from the index, thus eliminating the need to access the table at all. This can also be called an index-only query or a covering index.
- Indexing permits the server to ignore sorting by going through the rows in the desired order. As sorting costs a lot of money, reading the rows in the desired order is the faster option.
- Indexes allow the server to find groups of adjacent rows instead of individual rows. Many people believe that the purpose of the index is to find individual rows. However, finding individual rows leads to slowing down the process and random disk operations. Finding a group of rows that are all or most interesting is much better than finding rows individually.
If you are able to utilize these queries to design your queries and indexes, you can speed up your process pretty well.
How to Optimize MySQL WIth CloudPages
- Log in to Your CloudPages account.
- Choose the project in which you want to optimize MySQL
- After that, click List Server in the project dashboard, or simply click the server name.
- In the server dashboard, click on “Services”.
- Here you’ll see two services, “LiteSpeed” and “MariaDB”.
- Click on “MariaDB”.
- Click the green “Optimize MySQL” button on the top of the page.
- Next, click on “Generate Recommendations”. After going through all recommendations, click “”Apply Changes”.
And you’re done. With CloudPages, that is how you optimise MySQL. It will only take you a few minutes. If you don’t use CloudPages, then you can use the MySQL performance tuning tips mentioned above.
By going through this guide, you should be able to understand how to optimise MySQL and why tuning MySQL is so important. All developers should keep a close eye on all queries that are doing more work than needed. You can resolve this issue and improve data input and output speeds with the correct optimization technique.
Is there anything that you’d like to add? Feel free to share your thoughts in the comments section below.