Скачать или смотреть Understanding Why Your SQL Update Statement Keeps Affecting Rows: A PostgreSQL Guide

Discover the reasons why your SQL update statement might continue to affect rows even when re-run, and learn best practices to avoid unintended updates in `PostgreSQL`.
---
This video is based on the question https://stackoverflow.com/q/71206142/ asked by the user 'shazma' ( https://stackoverflow.com/u/16562053/ ) and on the answer https://stackoverflow.com/a/71206752/ provided by the user 'Serg' ( https://stackoverflow.com/u/6219979/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: When I perform an update - rows keep updating if I run the query again

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding Why Your SQL Update Statement Keeps Affecting Rows: A PostgreSQL Guide

When working with databases, encountering unexpected behavior can be frustrating, especially when executing an UPDATE statement in SQL. Imagine running an update query and believing that it should affect zero rows because the contents had already been updated, yet it consistently reports that several rows have been affected. This post aims to demystify such situations and provide insight into a common issue faced by developers and database administrators.

The Problem Explained

Consider the scenario where you are trying to update a table using the following SQL statement:

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

After executing this update query, you receive a result stating that "6 rows affected." However, when you run this exact query again, it keeps indicating "6 rows affected." This leads to confusion: why isn't the database recognizing that the rows have already been updated?

What Could Be Causing This?

The root of the issue lies in the condition within your UPDATE statement. More specifically, the COALESCE function and how you've structured your data can contribute to the unexpected results.

The Key Aspect: Duplicate References

If your source table (distance_tp) contains duplicate references (e.g., having multiple rows with the same ref), then your update can continuously affect rows. For example:

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

In this case, since the ref value is the same for multiple rows, the condition COALESCE(ead.distance,0) <> COALESCE(tp.distance,0) may always be true for one of the source rows no matter what the target value is. Consequently, even after an update, the query will continue to modify the distance field, leading to the repeated reporting of affected rows.

Solutions to Rectify the Issue

To avoid such situations and ensure your queries provide the expected outcomes, consider taking the following steps:

1. Checking for Duplicates

Ensure that your distance_tp table does not have duplicate records for the same ref. You can identify duplicates with a query like this:

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

If duplicates are found, you may need to decide how to handle them (e.g., removing duplicates or aggregating them).

2. Utilizing DISTINCT

If duplicates are valid within your business context, consider using the DISTINCT keyword when pulling data to ensure that only unique ref values are used in the update:

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

3. Review Your Logic

Ensure that your logic does not inadvertently allow for updates. If the intention is to update only when there is a change in value, make sure your conditions accurately reflect this, as shown in the corrected query above.

Conclusion

SQL update queries can sometimes yield unexpected results, particularly when working with duplicate data in your source tables. Understanding the impact of your conditions—particularly how duplicated references can cause queries to continue affecting rows—is critical. By following the recommendations outlined in this post, you should be able to prevent unwanted repeated updates in your PostgreSQL database, fostering cleaner data management and better performance outcomes.

If you have any further questions or require additional information, feel free to ask!