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Discover how to speed up your MySQL queries by optimizing the use of `NOT EXISTS` in your SQL statement. Improve performance while working with complex conditions and large datasets.
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This video is based on the question https://stackoverflow.com/q/76010031/ asked by the user 'Utku Dalmaz' ( https://stackoverflow.com/u/192525/ ) and on the answer https://stackoverflow.com/a/76013633/ provided by the user 'user1191247' ( https://stackoverflow.com/u/1191247/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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How to Optimize Your SQL Query: Solutions for Slow Performance with NOT EXISTS

When working with databases, especially large datasets, performance can become a critical issue. One common problem you may encounter is writing queries that take a long time to execute. Today, we will discuss a specific scenario where a query combining ORDER BY id DESC with a NOT EXISTS condition is running slow and how to effectively optimize it. If you've ever had a query that takes several seconds to complete, even with a reasonable number of rows in your table, this guide is for you.

The Problem

In this context, the SQL query in question is taking approximately 5 seconds to complete on a table with 30,000 rows. The query filters users based on activation status, excludes a specific user ID, and checks against the blockings table using the NOT EXISTS construct.

Here's a snippet of the original query:

[[See Video to Reveal this Text or Code Snippet]]

You might have noticed that removing the NOT EXISTS condition significantly speeds up the query, indicating that the performance hit stems from this particular part of the SQL statement.

Analyzing the Issue

Indexing Overview

Before diving into solutions, let's look at the current setup:

There is an index on users.id, and both blockings.user_id and blockings.blocked_id are indexed.

These indexes should ideally help in speeding up the querying process, but the presence of the NOT EXISTS can complicate things, especially with large data sets.

The Solution: Try a UNION

One potential solution is to restructure the NOT EXISTS clause using a UNION. By creating two separate selects within the NOT EXISTS clause, you can improve the query execution time. Here’s an improved version of the SQL query that incorporates this suggestion:

[[See Video to Reveal this Text or Code Snippet]]

The use of UNION ALL may allow for more efficient execution since MySQL has a better chance to optimize the query.

Another Approach: Split NOT EXISTS Conditions

You can also adopt another strategy by splitting the NOT EXISTS into two separate clauses. This can sometimes yield better performance, depending on how MySQL handles the specific execution plan. Here’s how it would look:

[[See Video to Reveal this Text or Code Snippet]]

This adjustment can avoid the complex execution that the combined query might lead to, allowing for more streamlined data retrieval.

Conclusion

Optimizing SQL queries is crucial for effective database management, especially when dealing with potentially slow commands like NOT EXISTS. By implementing strategies such as using UNION ALL or separating the conditions into distinct clauses, you can significantly improve your query performance.

Remember that every database setup is unique, so it's always a good practice to analyze the execution plans using EXPLAIN to gather insights about how your SQL statements are being executed.

Keep experimenting with your queries, and you'll be able to tackle performance issues swiftly. Happy querying!