How to Use MYSQL Explain to Improve MySQL Performance
Learn how to use the MYSQL EXPLAIN statement to improve your MySQL performance.
17:39 15 November 2022
As an open-source project, MYSQL is constantly being updated and improved by a community of developers, making it a reliable and robust option for anyone who needs a database management system. This motivates more than 200,000 businesses to make it an integral part of their workflow.
Over time, MYSQL can slow down for a variety of reasons. One reason is that it takes longer to find information as the database grows. Additionally, if many users access the database simultaneously, it can slow down the response time. If the database is not properly optimized, it can also cause a slowdown.
For businesses, it is important to have fast and efficient database performance. The MySQL EXPLAIN statement can be a valuable tool that can help businesses optimize outcomes by identifying areas where the database needs improvement.
What You Need To Know About MySQL Query Optimization
As a business, it's important to clearly understand how your MySQL database is being used and what might be causing any bottlenecks in performance. By optimizing queries, you can improve the overall speed and efficiency of your database.
There are a few key things to keep in mind when optimizing MySQL queries:
- Make sure that all necessary indexes are in place. Indexes can help speed up query execution by allowing the database to locate the needed data.
- Avoid using complex SQL statements if possible. If a query can be rewritten using simpler syntax, it will likely execute faster.
- Consider using caching to store frequently accessed data in memory. This can help reduce the need to repeatedly query the database, which can improve performance.
Introduction to MySQL EXPLAIN
EXPLAIN is a statement you can prepend to any query to see how MySQL will execute it. When you run an EXPLAIN on a query, MySQL will output information about the steps it will take to execute the query and some statistics about each step. This information can be very helpful in understanding why a particular query might be slow. This feature can be used with any query, including selects, inserts, updates, and deletes.
Let's take a look at a simple select query:
If you run EXPLAIN MYSQL query below, you'll see something like this:
This output shows that MySQL will execute this query by looking up the row with id=1 in table1. Since there is an index on the id column (the PRIMARY KEY), this should be a very fast operation. The output shows that MySQL expects this query to return only one row.
Now let's look at a more complex query:
If you run an EXPLAIN on this query, you'll see something like this:
This output tells us that MySQL will execute this query by first looking up the row with id=1 in table1 and then looking up the corresponding row in table2. Since there are indexes on both the id columns, this should be a fast operation. The output also shows that MySQL expects this query to return only one row.
Now let's look at a query that doesn't use an index:
If you run an EXPLAIN on this query, you'll see something like this:
This output reveals that MySQL will execute this query by scanning through all of the rows in table1 and checking to see if column1 is equal to the 'value.' Since there is no index on column1, this could be a very slow operation if table1 has a lot of rows. The output also shows that MySQL expects this query to return 100 rows.
What Information Can Be Withdrawn Using EXPLAIN?
Now that you've seen how to use EXPLAIN let's look at the other information it can provide.
The first piece of data is the select_type. This tells you the type of query that you're running. The most common type is SIMPLE, meaning the question is a single SELECT statement with no subqueries. Other types of queries include UNION, derived tables.
The next piece of information is the table type. This tells you how MySQL will access the table. The most common type is ALL, meaning that MySQL will scan the entire table. Other types include index, range, and ref.
The possible_keys column shows which indexes can be used to satisfy the query. In the first example, the possible keys are PRIMARY and index1. In the second example, the likely key is PRIMARY. In the third example, there are no possible keys because there are no indexes in column1.
The key column tells us which index MySQL decides to use. In the first example, the key is PRIMARY. In the second example, the key is index1. In the third example, there is no key because there are no indexes in column1.
The key_len column highlights the index length that MySQL decides to use. In the first example, the key_len is 4. In the second example, the key_len is 4. In the third example, there is no key_len because there are no indexes on column1.
The ref column shows which columns or values are used to match up rows in the joined tables. In the first example, the ref is const, which means that we match the id column in table1 with the id column in table2. In the second example, the ref is NULL because you're not matching up any columns. In the third example, the ref is NULL because you're not matching up any columns.
The rows column tells you the number of rows MySQL expects to scan through to satisfy the query. In the first example, the row is 1 because you only looked up one row in table1. In the second example, the row is 2 because you're looking up one row in table1 and one in table2. In the third example, the rows are 100 because you're scanning through all 100 rows in table1.
Finally, the Extra column contains information about how MySQL will execute the query. In the first example, the Extra column contains the text "Using index; Using join buffer," which tells you that MySQL will use an index to look up the row in table1 and then use a join buffer to look up the corresponding row in table2. In the second example, the Extra column contains the text "Using where," which shows that MySQL will use a full table scan because there is no index on column1. In the third example, the Extra column is empty because there is nothing special about this query.
Take Advantage of MYSQL Analyze Query
MYSQL analyze query is a database's command to analyze the tables and indexes. It can help you find problems with your tables or indexes and fix them.
This command can be used to find out the size of your tables and indexes and how much space they are taking up. It can also help you determine the fragmentation of your tables and indexes and how much time it takes to defragment them.
If you have a lot of data in your database or a lot of tables, it is a good idea to use MySQL analyze query to check the size of your database. This way, you can make sure that your database is manageable for your server.
Utilize Explain Visualizer
MYSQL Explain visualizer is a tool that can be used to help understand the output of the MySQL EXPLAIN command. It can be used to visualize the query plan and see how the different parts interact with each other.
The visualizer can be accessed from the MySQL Workbench home screen by selecting the "Explain Visualizer" option from the "Tools" menu.
Once the visualizer is open, the output of the EXPLAIN command can be pasted into the input box. The query plan will then be displayed in a graphical format, with each node in the plan represented by a circle.
The nodes are color-coded to indicate the type of operation that they represent. For example, green nodes represent operations performed on the data in the database, while blue nodes represent operations performed on the query results.
MySQL Explain in dbForge Studio for MySQL
The Query Profiler in dbForge Studio for MySQL is an excellent tool that can help you understand why your queries are running slowly and how you can tune them for better performance. With this tool, you can profile your queries and get a detailed report on the execution time, CPU usage, and other factors that affect the performance of your queries.
Besides, the Query Profiler can help you optimize your queries by providing suggestions on improving their performance. In this way, the MYSQL EXPLAIN plan can be valuable in helping you troubleshoot slow queries and optimize your database for better performance.
If you are not using the MySQL EXPLAIN extended modifier, you are missing out on valuable data that can help improve your query's performance. When used correctly, MySQL EXPLAIN can provide important information about how a query is executed and where bottlenecks exist.
Understanding what each execution stage is doing allows you to optimize your queries to run more efficiently.