FIND_IN_SET() vs. IN(): When Should I Use Each Function for Multi-Table Queries?

FIND_IN_SET() vs IN(): Understanding Query Differences

When querying data from multiple tables, it's crucial to understand how the syntax you use affects the results. Consider the following situation:

You have two tables, one for orders and one for companies. The orders table contains an attachedCompanyIDs column with comma-separated company IDs, and the company table contains CompanyID and name columns.

Query with FIND_IN_SET()

The query below enables you to retrieve all company names associated with a specific order:

SELECT name FROM orders, company
WHERE orderID = 1 AND FIND_IN_SET(companyID, attachedCompanyIDs)

This query successfully returns all company names: Company 1, Another Company, and StackOverflow.

Query with IN()

However, if you modify the query slightly by replacing FIND_IN_SET() with IN(), the results change:

SELECT name FROM orders, company
WHERE orderID = 1 AND companyID IN (attachedCompanyIDs)

In this case, the query only returns the first company name listed in the attachedCompanyIDs column: Company 1.

Understanding the Difference

The reason for this disparity lies in the way these two functions treat the attachedCompanyIDs column.

• FIND_IN_SET(): This function considers the entire string of attachedCompanyIDs and checks for the presence of companyID within it.
• IN(): This function interprets attachedCompanyIDs as a scalar value (e.g., a single number) and checks whether it matches the provided companyID.

Potential Issue with IN()

In your database example, attachedCompanyIDs is stored as a string. When used in the IN() function, it's automatically cast to an integer. However, this casting only considers the first digit before the comma. Therefore, only the first company ID in the attachedCompanyIDs list is considered.

Possible Solutions

• Use a direct table join: Join the orders and company tables on the companyID column to retrieve the company names. This approach ensures accurate results but may impact performance if there are numerous company IDs associated with each order.

• Use a more advanced query: If you have a limited number of values in the attachedCompanyIDs column, you can use a more complex query like this:

  SELECT name
  FROM orders
  CROSS JOIN (
    SELECT 1 AS pos
    UNION ALL
    SELECT 2 AS pos
    UNION ALL
    SELECT 3 AS pos
    UNION ALL
    SELECT 4 AS pos
    UNION ALL
    SELECT 5 AS pos
  ) q
  JOIN company
  ON companyID = CAST(NULLIF(SUBSTRING_INDEX(attachedCompanyIDs, ',', -pos), SUBSTRING_INDEX(attachedCompanyIDs, ',', 1 - pos)) AS UNSIGNED)

This query extracts individual company IDs from the attachedCompanyIDs string using the SUBSTRING_INDEX() function.

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