MYSQL is very slow when combing LIKE with EQUALS or IN, but not other OR operators [duplicate]

Are you tired of watching your MYSQL query crawl to a halt when combining LIKE with EQUALS or IN? You’re not alone! This phenomenon has left many a developer scratching their head, wondering why MYSQL is suddenly moving at a glacial pace. Fear not, dear reader, for today we’ll dive into the nitty-gritty of this issue and explore ways to optimize your queries for lightning-fast performance.

Why does MYSQL get slow when combining LIKE with EQUALS or IN?

Before we dive into the solution, let’s understand the root cause of the problem. When you combine LIKE with EQUALS or IN, MYSQL uses a different execution plan, which can lead to slower performance. Here’s what happens:

• LIKE scans the entire table: When you use LIKE, MYSQL has to scan the entire table to find matching patterns. This can be time-consuming, especially if your table is massive.
• EQUALS and IN add extra complexity: When you combine LIKE with EQUALS or IN, MYSQL has to perform additional checks, which further slows down the query.

But why does this happen specifically with EQUALS and IN, and not with other OR operators? The answer lies in the way MYSQL optimizes its queries.

Mysql’s Optimization Process

MYSQL’s optimization process involves several steps, including:

1. Parsing: MYSQL breaks down your query into smaller components.
2. Optimization: MYSQL analyzes the query and chooses the most efficient execution plan.
3. Execution: MYSQL executes the query using the chosen plan.

In the case of LIKE with EQUALS or IN, MYSQL chooses a suboptimal execution plan, leading to slower performance. But don’t worry, there are ways to optimize your queries and get MYSQL back up to speed!

Optimization Techniques for Combining LIKE with EQUALS or IN

Luckily, there are several techniques to optimize your queries and avoid the performance bottleneck. Here are some strategies to try:

Use indexes wisely

Indexes are a powerful tool in MYSQL’s optimization arsenal. By creating an index on the column used in the LIKE clause, you can significantly speed up your query.

CREATE INDEX idx_column_name ON table_name (column_name);

Note that indexes only work when the LIKE pattern starts with a constant string. If the pattern starts with a wildcard character (% or _), the index won’t be used.

Use a covering index

A covering index includes all columns used in the query, allowing MYSQL to retrieve the necessary data from the index alone, without accessing the underlying table.

CREATE INDEX idx_column_name ON table_name (column_name, equals_column_name, in_column_name);

This can be particularly useful when combining LIKE with EQUALS or IN, as it reduces the number of table scans.

Split the query into separate statements

Sometimes, breaking down the query into smaller, more manageable statements can improve performance. For example:

SELECT * FROM table_name WHERE column_name LIKE '%pattern%';
SELECT * FROM table_name WHERE equals_column_name = 'value';
SELECT * FROM table_name WHERE in_column_name IN ('value1', 'value2');

Instead of:

SELECT * FROM table_name WHERE column_name LIKE '%pattern%' AND equals_column_name = 'value' AND in_column_name IN ('value1', 'value2');

This approach can be more efficient, especially if each individual query is optimized with indexes.

Use UNION ALL instead of OR

When combining LIKE with EQUALS or IN using OR, MYSQL has to perform a union of the two result sets. This can lead to slower performance. Instead, use UNION ALL to combine the result sets:

SELECT * FROM table_name WHERE column_name LIKE '%pattern%'
UNION ALL
SELECT * FROM table_name WHERE equals_column_name = 'value' AND in_column_name IN ('value1', 'value2');

This approach can be more efficient, especially if the result sets are small.

Optimize your LIKE patterns

Lastly, optimize your LIKE patterns to reduce the number of potential matches. For example:

SELECT * FROM table_name WHERE column_name LIKE 'pattern%';

Instead of:

SELECT * FROM table_name WHERE column_name LIKE '%pattern%';

By reducing the number of potential matches, you can significantly speed up your query.

Conclusion

In conclusion, combining LIKE with EQUALS or IN can lead to slower performance due to MYSQL’s optimization process. However, by using indexes wisely, creating covering indexes, splitting the query into separate statements, using UNION ALL instead of OR, and optimizing your LIKE patterns, you can significantly improve the performance of your MYSQL queries. Remember, a well-optimized query is key to a happy developer and a happy database!

Techinique	Description	Example
Use indexes wisely	Create an index on the column used in the LIKE clause	CREATE INDEX idx_column_name ON table_name (column_name);
Use a covering index	Create an index that includes all columns used in the query	CREATE INDEX idx_column_name ON table_name (column_name, equals_column_name, in_column_name);
Split the query into separate statements	Break down the query into smaller, more manageable statements	SELECT * FROM table_name WHERE column_name LIKE '%pattern%';
Use UNION ALL instead of OR	Combine result sets using UNION ALL instead of OR	SELECT * FROM table_name WHERE column_name LIKE '%pattern%' UNION ALL SELECT * FROM table_name WHERE equals_column_name = 'value' AND in_column_name IN ('value1', 'value2');
Optimize your LIKE patterns	Reduce the number of potential matches by optimizing your LIKE patterns	SELECT * FROM table_name WHERE column_name LIKE 'pattern%';

By following these techniques, you’ll be well on your way to optimizing your MYSQL queries and avoiding the performance bottleneck caused by combining LIKE with EQUALS or IN. Happy optimizing!

Frequently Asked Question

Mysql is very slow when combining LIKE with EQUALS or IN, but not with other OR operators. Let’s dive into the reasons and solutions.