How to Effectively Manage Duplicate Rows in SQL Joins Using ROW_NUMBER()

Learn how to handle duplicate rows when joining two datasets in SQL. This guide uses `ROW_NUMBER()` to filter out unwanted duplicates while efficiently managing your data.
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This video is based on the question https://stackoverflow.com/q/65821103/ asked by the user 'Lynn' ( https://stackoverflow.com/u/5942100/ ) and on the answer https://stackoverflow.com/a/65821258/ provided by the user 'Venkataraman R' ( https://stackoverflow.com/u/634935/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Handling Conditional Joins and Duplicate Rows in SQL

When working with two datasets (df1 and df2), one common challenge is effectively joining them while applying conditions to eliminate duplicates based on specific criteria. In this guide, we'll explore how to do just that by using SQL's powerful ROW_NUMBER() function.

The Problem

Suppose you have two datasets:

df1 contains version data with host records.

df2 includes names and purposes associated with those versions.

Here are some example records from both datasets:

Dataset 1: df1

[[See Video to Reveal this Text or Code Snippet]]

Dataset 2: df2

[[See Video to Reveal this Text or Code Snippet]]

When you join these datasets on specified conditions (df1.version = df2.name and df1.date = df2.date), you receive the following result:

[[See Video to Reveal this Text or Code Snippet]]

However, the desired result shows only one row for entries where duplicate hosts exist. In this case, we want to filter the results so that only unique host rows are displayed based on specific purposes (hi or cat).

Solution Overview

To achieve the desired output, we can leverage the SQL ROW_NUMBER() function to assign a unique rank to each row based on a set of conditions. This allows us to select only the first occurrence of duplicates, effectively filtering our results.

Step-by-Step Breakdown

Define a Common Table Expression (CTE) or use a derived table to rank rows based on the host.

Apply ROW_NUMBER() to partition the results by host and order them according to your conditions.

Select only the rows where the rank is 1 to eliminate duplicates.

SQL Implementation

Here's how you can structure your SQL query using a CTE:

[[See Video to Reveal this Text or Code Snippet]]

Alternative Method: Without CTE using a Derived Table

If you prefer not to use a CTE, you can achieve the same outcome with a derived table as follows:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

By utilizing the ROW_NUMBER() function in your SQL queries, you can effectively manage duplicates and ensure that your data returns only the rows you need. This approach not only streamlines your results but also enhances the integrity of your data analysis workflow. Whether you opt for a CTE or a derived table method, both techniques are powerful tools in your SQL arsenal.

Make sure to apply these practices in your data management tasks and see the difference in the quality of your outcomes!

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