Search for Specific Characters: Escaping Wildcards in T-SQL

There are two main methods to escape a percent sign in T-SQL:

2. Using the ESCAPE clause: This method allows you to define a specific character as an "escape character." Any character following the escape character will be interpreted literally, even if it's normally a wildcard. Here's how it works:

   • Construct your search pattern with the percent signs you want to match literally.
   • Add the ESCAPE keyword followed by the chosen escape character (e.g., ESCAPE '!').

For example:

SELECT * FROM prices WHERE discount LIKE '%80!% ESCAPE '!'

This query would find rows in the "prices" table where the "discount" column contains "80%". The exclamation mark (!) acts as the escape character, making the following percent sign a literal character.

This code searches for customer names that start with "Special Offer" followed by a literal percent sign:

SELECT * FROM Customers WHERE Name LIKE 'Special Offer[%]'

Here, the percent sign within square brackets is interpreted as a literal character, not a wildcard.

Example 2: Using ESCAPE Clause

This code searches for product descriptions containing "20% off":

SELECT * FROM Products WHERE Description LIKE '20!% off' ESCAPE '!'

The exclamation mark (!) is defined as the escape character using the ESCAPE clause. This makes the following percent sign a literal character, searching for "20% off" exactly.

Example 3: Combining LIKE and WHERE with Escaped Percent

This code finds orders with a total amount greater than $100 and a discount code containing "50%":

SELECT * FROM Orders
WHERE TotalAmount > 100 AND DiscountCode LIKE '%50!%' ESCAPE '!'

1. Conditional Logic (if data allows):

If your data allows for some restructuring, you could potentially avoid using wildcards altogether. For example, instead of storing "Discount 50%" in a column, you could have separate columns for "Discount Type" (e.g., "Percentage") and "Discount Value" (e.g., 50). This eliminates the need for escaping percent signs and simplifies your queries.

1. Stored Procedures (for complex logic):

For very complex scenarios where escaping might become cumbersome, you could consider creating a stored procedure. This procedure could handle the logic of searching for specific patterns with percent signs, potentially using dynamic SQL or string manipulation techniques within the procedure itself. This approach can be useful for encapsulating complex search logic and improving code readability.

However, it's important to note that these alternative methods come with their own drawbacks:

• Conditional Logic: Restructuring data might not always be feasible and can introduce redundancy.
• Stored Procedures: Stored procedures add an extra layer of complexity and require additional maintenance.