SQL Performance: When Should I Use OR vs. UNION?

SQL performance: UNION vs. OR comparison

A recent article on SQL statement optimization raised performance issues regarding the use of OR and UNION. While the author recommends replacing OR with UNION to improve performance, closer examination reveals that not all OR statements require this conversion.

Use OR

The OR operator combines conditions so that if either condition is true, the result is true. In SQL, OR can be applied to columns and rows.

For example, the following query retrieves rows where the company is 'bbc' or 'itv':

<code class="language-sql">select username from users where company = 'bbc' or company = 'itv';</code>

This query is equivalent to:

<code class="language-sql">select username from users where company IN ('bbc', 'itv');</code>

MySQL can effectively leverage the index on the company column to perform this query without using UNION.

Use UNION

UNION combines the results of multiple queries. When applied to rows, UNION retrieves rows that meet one or more specified criteria, but it excludes duplicate rows.

In the following query:

<code class="language-sql">select username from users where company = 'bbc' 
union
select username from users where city = 'London';</code>

UNION enables each subquery to utilize its own index to optimize the search. UNION then combines the results of the two subqueries.

When to use OR or UNION

OR is more suitable when the following conditions are met:

• The condition involves the same column
• An index exists on the specified column

UNION is more efficient when the following conditions are met:

• The condition involves different columns
• No suitable index exists for the specified condition

SORT AND UNION

UNION incurs sorting overhead to eliminate duplicate rows. However, this overhead usually affects a small proportion of the results. The cost of sorting is usually less than the optimization gained by using a subquery index.

Therefore, determining the most appropriate method (OR vs. UNION) requires careful consideration of the specific data and search criteria. Benchmarking both approaches using MySQL Query Analyzer can provide conclusive performance insights.

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