How can we remove duplicates from two columns in an SQL database?

 To remove duplicates from two columns in an SQL database, you can use a combination of a DELETE statement with a JOIN or a CTE (Common Table Expression) along with a ROW_NUMBER() function to identify duplicate rows and then remove them.

Here’s how you can approach it:

Assumptions:

• You have a table called your_table.
• You want to remove rows where the combination of values in column1 and column2 is duplicated.

Step-by-Step Approach

1. Using a CTE with ROW_NUMBER()

You can use ROW_NUMBER() to assign a unique number to each row within the same column1 and column2 values, then delete the duplicates (where the ROW_NUMBER is greater than 1).

WITH CTE AS (
    SELECT
        *,
        ROW_NUMBER() OVER (PARTITION BY column1, column2 ORDER BY id) AS rn
    FROM
        your_table
)
DELETE FROM your_table
WHERE id IN (
    SELECT id
    FROM CTE
    WHERE rn > 1
);

• Explanation:
  • The ROW_NUMBER() function assigns a sequential number to each row within the same column1 and column2 values. The PARTITION BY column1, column2 ensures that duplicates (same values in both columns) are grouped together.
  • The ORDER BY id ensures the first row in each group (based on id) gets ROW_NUMBER = 1, while the duplicates get numbers greater than 1.
  • The DELETE query removes the rows where rn > 1, i.e., the duplicates.

2. Using a JOIN with a Subquery

Alternatively, you can delete duplicates using a JOIN:

DELETE t1
FROM your_table t1
JOIN (
    SELECT MIN(id) AS id, column1, column2
    FROM your_table
    GROUP BY column1, column2
) t2
ON t1.column1 = t2.column1
AND t1.column2 = t2.column2
AND t1.id > t2.id;

• Explanation:
  • This query selects the minimum id for each combination of column1 and column2 (this will keep the "first" occurrence).
  • Then, it joins the table (your_table t1) with the subquery (t2) and deletes rows where the id is greater than the minimum id for that combination (i.e., the duplicates).

Notes:

• Be cautious when performing DELETE operations. It’s always a good idea to first run the SELECT part of the query (before the DELETE) to verify that you are identifying the correct rows.
• If you are working with large datasets, consider testing the query on a smaller subset or backup data first.