Understanding Duplicate Rows in SQL

Introduction

When working with databases, it’s common to encounter duplicate rows that can be removed or handled in a specific way. In this article, we’ll explore how to delete duplicate rows based on two values in SQL, specifically focusing on the ROWID approach.

The Problem with the Given Solution

The original solution provided uses the ROWID column to identify and delete duplicate rows. However, this approach has limitations, especially when dealing with large datasets or tables with multiple columns. In the example provided, the code deletes all rows where the till_id is repeated, but it doesn’t differentiate between full duplicates.

We’ll delve into the details of why this solution works and how we can improve it to handle duplicate rows based on two values.

Understanding the Original Solution

Let’s examine the original SQL query that deletes duplicate rows:

SELECT till_id, total, COUNT(*) AS CNT
FROM till_total
GROUP BY till_id, total
HAVING COUNT(*) > 1
ORDER BY till_id;

This query uses a GROUP BY clause to group rows by the till_id and total columns. The COUNT(*) aggregation function is used to count the number of rows in each group.

The HAVING clause filters the results to only include groups with more than one row (i.e., full duplicates). Finally, the query orders the results by the till_id.

However, this solution has a major flaw: it deletes all rows where the till_id is repeated, regardless of whether they are full duplicates or not.

The ROWID Approach

The original answer provides an alternative solution using the ROWID column. Here’s how it works:

DELETE FROM till_total a
  2  WHERE a.rowid > (SELECT MIN(b.rowid)
  3                   FROM till_total b
  4                   WHERE b.till_id = a.till_id
  5                     AND b.total = a.total
  6                  );

This query uses a subquery to find the minimum ROWID value for each group of rows with the same till_id and total. The outer query then deletes all rows where the ROWID is greater than this minimum value.

However, as mentioned earlier, this solution has limitations. It doesn’t handle cases where there are multiple full duplicates, and it can lead to performance issues when dealing with large datasets.

Handling Duplicate Rows Based on Two Values

To handle duplicate rows based on two values, we need a more sophisticated approach that takes into account the relationships between columns. One way to achieve this is by using a combination of aggregate functions and subqueries.

Here’s an example solution:

WITH full_duplicates AS (
  SELECT till_id, total,
         COUNT(*) OVER (PARTITION BY till_id, total) AS count
  FROM till_total
)
DELETE FROM till_total t1
  2  WHERE t1.till_id = (SELECT till_id FROM full_duplicates t2
                        WHERE t2.total = t1.total AND t2.count > 1);

This query uses a Common Table Expression (CTE) to identify full duplicates based on the till_id and total columns. The CTE calculates the count of rows for each group using an aggregate function.

The outer query then deletes all rows where the till_id matches a row with a count greater than 1, effectively removing full duplicates.

Conclusion

Deleting duplicate rows based on two values in SQL requires a thoughtful approach that takes into account the relationships between columns. While the original solution using ROWID has limitations, we can improve it by using aggregate functions and subqueries to handle duplicate rows more effectively.

By understanding the underlying mechanisms of SQL and how to manipulate data using aggregate functions and subqueries, you’ll be better equipped to tackle complex data manipulation tasks in your own projects.

Last modified on 2025-03-10