Is a LEFT JOIN Really Faster Than an INNER JOIN in SQL Server?

Performance comparison of LEFT JOIN and INNER JOIN in SQL Server

Uncovering the myth of LEFT JOIN’s speed advantage

There is a common misconception that LEFT JOIN is inherently faster than INNER JOIN in SQL Server. However, this assumption is fundamentally wrong.

The truth comes out

Actually, LEFT JOIN requires more processing time than INNER JOIN. By definition, a LEFT JOIN contains the operations of an INNER JOIN, but it also performs the additional step of extending the result with NULL values. It is worth noting that LEFT JOIN often returns more rows, further causing increased execution time due to larger result sets.

Find out the root cause

Most of the time, performance barriers to database queries do not stem from the choice between INNER JOIN and LEFT JOIN. The underlying problem is usually poor indexing or lack of a suitable index. The problem can be exacerbated when multiple tables are involved (9 tables in this case).

Pattern Check

In order to provide specific guidance, it is crucial to examine the provided schema. Without a pattern, it's difficult to pinpoint the exact cause of slow performance.

Exceptions

Theoretically, there is a situation where LEFT JOIN may indeed be faster than INNER JOIN:

• Extremely small table size (less than 10 rows)
• No suitable index

In this case, SQL Server may choose to perform a nested loop on the LEFT JOIN instead of using the more efficient hash matching on the INNER JOIN. However, this situation is extremely unlikely to occur in actual database operations.

Optimization considerations

Rather than relying on the alleged speed difference between LEFT JOIN and INNER JOIN, it is better to solve the core problem of insufficient indexing to optimize database queries. Creating appropriate indexes and ensuring adequate index coverage can significantly improve performance.

Conclusion

Misunderstandings about the performance advantages of LEFT JOIN over INNER JOIN may lead to optimization in the wrong direction. Focusing on proper indexing and database design principles will ultimately lead to the desired performance improvements.

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