9/27/2023 0 Comments Mysql like vs substring![]() Solution: Please do use the WHERE clause, and use EXPLAIN to see the performance. Both scenario's:ġ/ If you do SELECT field FROM table WHERE field LIKE "%value%", MySQL will scan the entire table, and only send the fields containing "value".Ģ/ If you do SELECT field FROM table and then have your application (in your case PHP) filter only the rows with "value" in it, MySQL will also scan the entire table, but send all the fields to PHP, which then has to do additional work. I say that doing a WHERE field LIKE "%value%" is slower than WHERE field LIKE "value%" if the column field has an index, but this is still considerably faster than getting all values and having your application filter. Updated answer to reflect question update: Matches any number of characters including zero. ![]() This is a table which describes the wildcards used with MySQL LIKE operator. In a more technical note, LIKE operator does pattern matching using simple regular expression comparison. By default, the search will be case-insensitive. MySQL LIKE operator along with WILDCARDS finds a string of a specified pattern within another string. For case-sensitive matches, declare either. As the second query applies an additional function, I would. LIKE performs case-insensitive substring matches if the collation for the expression and pattern is case-insensitive. The difference - the first query groups the data by groupid the second by substr (groupid,1,1). Whether the search is case-sensitive or not depends on how you stock the data, especially what COLLATION you use. select max (round (b.avgquotient,2)) as answer from (SELECT AVG (sqlquotient) as avgquotient FROM Students GROUP BY substr (groupid,1,1) )as b Runtime 0.000459 sec. To get the columns that don't match, simply put a NOT in front of the like: WHERE textcolumn NOT LIKE "%SUBSTRING%". It depends on the field type - a textarea usually won't be saved as VARCHAR, but rather as (a kind of) TEXT field, so you can use the MATCH AGAINST operator. Also, the execution plan shows a recommended index for Method 2 that could improve its performance. ![]() Well, you can always try WHERE textcolumn LIKE "%SUBSTRING%" - but this is guaranteed to be pretty slow, as your query can't do an index match because you are looking for characters on the left side. Method 1: ON tB.columnB like tA.columnA '' Method 2: ON substr (tB.columnB,1,2) tA.columnA The query execution plan has a lot less steps using Method 1 compared to Method 2, however, it looks like Method 2 executes much faster.
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