![]() This statement would then return all suppliers whose supplier_name is G%. MySQL then assumes that the escape character is "\" which results in MySQL treating the % character as a literal instead of a wildcard. Since we didn't specify an escape character, MySQL assumes that the "\" is the escape character. Please note that you can only define an escape character as a single character (length of 1). You can do this using an Escape character. Let's say you wanted to search for a % or a _ character in the MySQL LIKE condition. ![]() These examples deal specifically with escaping characters in MySQL. It is important to understand how to "Escape Characters" when pattern matching. The example above, would retrieve potentially 10 records back (where the missing value could equal anything from 0 to 9). You might find that you are looking for an account number, but you only have 5 of the 6 digits. ![]() For example, it could return suppliers whose supplier_name is 'Smith', 'Smyth', 'Smath', 'Smeth', etc. This MySQL LIKE condition example would return all suppliers whose supplier_name is 5 characters long, where the first two characters are 'Sm' and the last two characters are 'th'. Remember that _ wildcard is looking for only one character. Next, let's explain how the _ wildcard (underscore wildcard) works in the MySQL LIKE condition. If you want to learn more about regular expressions, I recommend as a good reference site.Example - Using _ wildcard (underscore wildcard) However, I imagine performance could be an issue with bigger databases, larger fields, greater record counts, and more complex filters.Īs always, use logic above as it makes sense. Regarding performance, I ran some minor tests against an existing table and found no differences between my variations. However, you can also mix these types of statements as you can see in the second example listed. This allows you to add specific matches with wildcard matches in the same expression. In the first example above, I use ^9999$ to indicate exact match. However, these expressions did not appear to yield the desired results. I experimented with using negating patterns, forward looking patterns, and so on. Notice I separated the NOT set in a separate WHERE filter. OR Mixed Alternative: SELECT * FROM fiberbox WHERE field REGEXP '1740 |1938 ' Use REGEXP Alternative: SELECT * FROM fiberbox WHERE field REGEXP '1740 |1938 |^9999$' You'll need to test your patterns and see what works.įinally, To Accomplish Multiple LIKE and NOT LIKE filters: SELECT * FROM fiberbox WHERE field LIKE '40 %' ![]() NOTE: Not all regex patterns appear to work in MySQL statements. There are more efficient ways to narrow down specific matches, but that requires more review of Regular Expressions. Inside () with * (.*) adds a repeating pattern indicating any number indicates any single character, except line breaks. Placing (.*) behaves much like the % wildcard. Placing $ after the value indicates end of line. Placing ^ in front of the value indicates start of the line. Use: SELECT * FROM fiberbox WHERE field REGEXP '^1740 |1938 $|1940 (.*) test' To Accomplish LIKE with Controlled Wildcard Placement: SELECT * FROM fiberbox WHERE field LIKE '1740 %' If you need more control over placement of the wildcard, use some of these variants: Typically, REGEXP will require wildcard expressions such as (.*)1740 (.*) to work as 40 %. Values within REGEXP quotes and between the | (OR) operator are treated as wildcards. Use REGEXP Alternative: SELECT * FROM fiberbox WHERE field REGEXP '1740 |1938 |1940 ' To Accomplish multiple LIKE filters with Wildcards: SELECT * FROM fiberbox WHERE field LIKE '40 %' To add to this, here are some things I observed for those interested in using REGEXP: Paul Dixon's answer worked brilliantly for me.
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