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Скачать или смотреть Converting MSSQL Date Range Selection to MySQL Syntax

  • vlogize
  • 2025-07-19
  • 0
Converting MSSQL Date Range Selection to MySQL Syntax
What's the equivalent syntax in MySQL for selecting date ranges by YEAR based on MSSQL syntax?mysqlsqlmysql workbench
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Описание к видео Converting MSSQL Date Range Selection to MySQL Syntax

Learn how to effectively select date ranges in MySQL, replacing MSSQL syntax with MySQL compatible queries for improved accuracy.
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This video is based on the question https://stackoverflow.com/q/67501393/ asked by the user 'wawawa' ( https://stackoverflow.com/u/10581944/ ) and on the answer https://stackoverflow.com/a/67501825/ provided by the user 'Gordon Linoff' ( https://stackoverflow.com/u/1144035/ ) 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: What's the equivalent syntax in MySQL for selecting date ranges by YEAR based on MSSQL syntax?

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.

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Selecting Date Ranges in MySQL: Transitioning from MSSQL Syntax

When it comes to working with databases, particularly when switching from one SQL variant to another, understanding how to properly translate queries is crucial. A common challenge arises when selecting records within a specific date range. In this post, we will dive into translating an MSSQL date range selection into equivalent MySQL syntax, ensuring that your queries return accurate results.

The Problem: MSSQL Date Range Selection

Let’s consider a practical scenario. You have the following MSSQL code that successfully retrieves records from the past two years up to a specific date:

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

This works well and returns dates that fall within the two-year range ending on May 12, 2021. However, as you attempt to convert this to MySQL, you find that the syntax you use doesn’t yield the same precision.

Here's the MySQL attempt you've made:

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

This query, however, returns results outside the two-year range, indicating that there’s a flaw in the translation process.

The Solution: A More Accurate MySQL Syntax

To achieve the desired result in MySQL, it’s important to omit the BETWEEN keyword when querying date ranges. Using BETWEEN can lead to unexpected selections, particularly if column_1 includes time components. Instead, here's a recommended approach to ensure you accurately select dates from two complete years:

Updated MySQL Query

Here’s how your MySQL syntax should be structured:

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

Explanation of the Code

Start Date Calculation: '2021-05-13' - INTERVAL 2 YEAR calculates the starting point for your date range, effectively two years before May 13, 2021.

End Date Handling: The condition column_1 < '2021-05-13' ensures that your query excludes the end date but includes the entirety of the two years prior.

Key Benefits of This Approach

Clarity: This method clarifies the logic behind date selection, reducing confusion when dealing with date and time components.

Precision: By avoiding the potential traps of BETWEEN, you gain precise control over the limits of your date range.

Conclusion

Translating date range selections from MSSQL to MySQL requires meticulous attention to detail. By restructuring your query to avoid the use of BETWEEN and employing clear conditions, you can ensure that your date selections are both accurate and efficient. This not only helps in maintaining data integrity but also enhances the performance of your SQL queries.

For developers and database administrators transitioning between SQL dialects, mastering these nuances is essential for successful database management.

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