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Скачать или смотреть How to Compare Date Range by Month and Year in Oracle using OUTSYSTEMS

  • vlogize
  • 2025-08-22
  • 2
How to Compare Date Range by Month and Year in Oracle using OUTSYSTEMS
Compare date Range by Month (Integer) and Year (Integer)javasqloracledatetimeoutsystems
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Описание к видео How to Compare Date Range by Month and Year in Oracle using OUTSYSTEMS

Learn how to effectively validate date ranges using month and year integers in Oracle with OUTSYSTEMS. Discover methods for accurate filtering of date ranges in a database context.
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This video is based on the question https://stackoverflow.com/q/64146461/ asked by the user 'PedroEstevesAntunes' ( https://stackoverflow.com/u/11671658/ ) and on the answer https://stackoverflow.com/a/64146507/ provided by the user 'GMB' ( https://stackoverflow.com/u/10676716/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Comparing Date Ranges by Month and Year in Oracle with OUTSYSTEMS

When working with date ranges in databases, especially when dealing with integer representations of months and years, a common challenge arises: how to filter records that fall within a specific month and year. This guide tackles this issue, specifically within the context of OUTSYSTEMS and Oracle, providing both explanations and practical solutions.

The Problem

Imagine you are tasked with validating date ranges where both the month and year are specified as integers. You have two date fields, Start Date and End Date, and need to determine which of those dates fall within a given month and year combination.

Here's the scenario:

You have a specific month and year as integer inputs.

You need to extract records from the database that fall within this month and year range.

For example, consider the following Start Date and End Date values from a database:

Record 1: Start Date: 2020-08-16, End Date: 2020-10-14

Record 2: Start Date: 2019-11-01, End Date: 2020-08-15

If you are looking for data for July 2020 (with Month = 7 and Year = 2020), you wouldn't find any matching records. However, if you were looking for data in August 2020, you’d need both records because at least part of their ranges overlaps with that month.

Solution Breakdown

To solve this problem effectively, we will refine the approach to gathering results based on the provided month and year. Let's break it down into organized sections.

Basic Idea: Convert Dates to Integer Format

The simplest way to approach this involves converting your Start Date and End Date into an integer format that combines the year and month. This format can be generated as follows:

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

For instance:

For August 2020, this would yield 202008.

Using the Between Clause

One possible SQL query could look like this:

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

This would allow you to filter results that fall within both the start and end date's month and year.

Alternative Options

If you're less inclined to use BETWEEN, an alternative query structure is:

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

Important Considerations

Performance: Be cautious as applying functions on columns (like year() and month()) can slow down query performance, especially on large datasets.

Date Function Variance: Since date functions are highly vendor-specific, make sure to adjust your SQL code based on the database system you are using. For Oracle, functions like EXTRACT(YEAR FROM date) or EXTRACT(MONTH FROM date) might be useful.

Conclusion

By following the structured approach above, you should be able to effectively validate and compare date ranges using integers for month and year in OUTSYSTEMS with Oracle. This methodology provides a clear pathway to ensure you retrieve the relevant records tied to your specified dates without inefficiencies in your query.

If you encounter specific issues while implementing the solution, don’t hesitate to ask for further clarification! Your date handling challenges can be resolved efficiently with thoughtful SQL practices.

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