Скачать или смотреть Solve Your SQL Problem: Merge Rows Based on Identical Strings in MySQL

Learn how to properly aggregate rows in SQL queries when the strings are the same, ensuring accurate results for your website stats page.
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How to Merge Rows in SQL When Strings are Identical

If you're working with SQL in MySQL, you may sometimes encounter a situation where your data doesn't aggregate as you expect it to, especially when you want to merge rows with identical string values. This scenario can lead to confusion and inaccurate results, particularly when you're trying to compile statistics. In this guide, we'll walk through an example of this problem and provide a clear solution to help you fix your SQL queries efficiently.

The Problem

Imagine you're building a stats page for your website, and you have two tables that contain information about DJs and the hours they worked in a specific week. After running your query, you discover that even though the names are the same, the results are not merged correctly. For example:

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

In this case, Jack's results from different tables are displayed separately instead of merged into a single entry.

Understanding the Existing Query

Initially, the query you have is as follows:

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

This query attempts to count the number of hours worked by each DJ from two different tables and merge them. However, due to the use of UNION ALL and separate aggregations, it doesn't yield the desired merged output.

The Solution

Streamlined Approach

To achieve the correct results, you only need to aggregate once after combining both tables into one set. You can do this by modifying your query as follows:

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

Breakdown of the Solution

Combining Tables: The inner query combines the two tables using UNION ALL, which allows you to include all records from both tables, even if they have duplicates. This is crucial for ensuring that names are counted together.

Grouping Results: After merging, we apply GROUP BY on t.dj_1 to consolidate the entries for DJs with the same name.

Counting Records: The COUNT(*) function counts all the occurrences of each DJ, giving you the total hours worked.

Ordering the Results: Finally, using ORDER BY uren DESC sorts the results in descending order based on the count of hours, allowing you to see the DJs who worked the most at the top.

Conclusion

By restructuring your query to aggregate after combining both tables, you can effectively merge rows based on identical strings in MySQL. This not only simplifies your SQL queries but also ensures accurate representation of your data, which is essential for a reliable stats page.

Now, you are equipped to handle similar scenarios with confidence! If you have further questions on SQL or MySQL, feel free to reach out.