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Learn how to efficiently remove duplicate rows from your PostgreSQL tables using window functions and temporary tables.
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How to Delete Duplicate Rows in PostgreSQL Using Window Functions

Managing data efficiently is crucial in any database system, and one common issue that developers face is dealing with duplicate rows. If you're using PostgreSQL and encounter duplicates in your tables, you may be wondering how to effectively remove them. In this post, we will focus on a specific scenario: deleting duplicate rows based on the emp_name column in an employee table.

Understanding the Issue

Consider the following SQL setup with our employee table, which contains the employee ID, name, and department ID:

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In this table, the rows for smith stuart, james ward, and adam black appear more than once. You want to eliminate these duplicates based on the emp_name column.

The Initial Attempt

You may have tried the following code using a Common Table Expression (CTE):

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However, this code returns an error, indicating that you cannot delete from a CTE: 'ERROR: relation "cte_table" does not exist'. This is a common pitfall when using CTEs in SQL.

The Solution: Using Temporary Tables

Instead of using a CTE, the more effective approach is to utilize a temporary table. This allows you to store the results of your query in a table format that can be modified—unlike a CTE, which is designed for read-only access. Here’s how you can approach it:

Step 1: Create a Temporary Table

To capture the duplicate values with their assigned row numbers, you can create a temporary table as follows:

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Step 2: Delete Duplicates

Once you have your temporary table set up, you can easily delete the duplicates:

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Step 3: Review the Results

Now that the duplicates have been deleted from your temporary table, you can review these changes. If desired, you can insert the distinct records back into your original employee table or simply replace the original table with the temporary table content.

Conclusion

Handling duplicate rows in a PostgreSQL database can be achieved efficiently using window functions combined with temporary tables. By following the method outlined above, you can streamline your database management and ensure that your datasets are clean and accurate.

Start De-duplicating!

If you're facing similar issues in your own databases, don't hesitate to implement this approach. With practice, you’ll be able to maintain tidy tables and enhance the integrity of your data effortlessly. Happy coding!