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copied!<p>You can do it by in one query by stringing together the individual LIKEs with ORs:</p> <pre><code>SELECT * FROM tablename WHERE column LIKE 'M510%' OR column LIKE 'M615%' OR column LIKE 'M515%' OR column LIKE 'M612%'; </code></pre> <p>Just be aware that things like LIKE and per-row functions don't always scale that well. If your table is likely to grow large, you <em>may</em> want to consider adding another column to your table to store the first four characters of the field independently.</p> <p>This duplicates data but you can guarantee it stays consistent by using insert and update triggers. Then put an index on that new column and your queries become:</p> <pre><code>SELECT * FROM tablename WHERE newcolumn IN ('M510','M615','M515','M612'); </code></pre> <p>This moves the cost-of-calculation to the point where it's necessary (when the data changes), <em>not</em> every single time you read it. In fact, you could go even further and have your new column as a boolean indicating that it was one of the four special types (if that group of specials will change infrequently). Then the query would be an even faster:</p> <pre><code>SELECT * FROM tablename WHERE is_special = 1; </code></pre> <p>This tradeoff of storage requirement for speed is a useful trick for larger databases - generally, disk space is cheap, CPU grunt is precious, and data is read far more often than written. By moving the cost-of-calculation to the write stage, you amortise the cost across all the reads.</p>

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