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Скачать или смотреть How to Combine Two Tables in SQL with Different Column Structures

  • vlogize
  • 2025-05-26
  • 0
How to Combine Two Tables in SQL with Different Column Structures
Combine 2 table with both like and unlike columnssqlms access
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Описание к видео How to Combine Two Tables in SQL with Different Column Structures

Learn how to effectively join two tables with both similar and different columns using SQL UNION for comprehensive data analysis.
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This video is based on the question https://stackoverflow.com/q/70339757/ asked by the user 'Chris Wilson' ( https://stackoverflow.com/u/11735692/ ) and on the answer https://stackoverflow.com/a/70340030/ provided by the user 'June7' ( https://stackoverflow.com/u/7607190/ ) 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: Combine 2 table with both like and unlike columns

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.
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Combine Two Tables in SQL with Different Column Structures

When working with databases, it’s common to encounter situations where you need to merge data from different tables. This can often pose challenges, especially when the columns do not perfectly align. If you have faced this dilemma, you're not alone. In this guide, we’ll go through the step-by-step process of combining two tables that have both similar and differing columns, ensuring that you can achieve your desired outcomes effectively.

The Problem: Joining Tables with Different Columns

Imagine you have two tables in your database:

Table 1 consists of the following columns:

Date

ClientID

ClientName

Revenue

Cost1A

Cost1B

Cost1C

Table 2 has these columns:

Date

ClientID

ClientName

Revenue

Cost2

You might find yourself needing to merge these tables into a single result, as shown below:

Wanted Result:

DateClientIDClientNameRevenueCost1ACost1BCost1CCost212/13/2021001ClientA1001010012/13/2021001ClientA2501010012/13/2021002ClientB25001015100012/13/2021003ClientC1001012/13/2021003ClientC2501012/13/2021001ClientA2510The goal is to create a result that combines these tables effectively, keeping data organized while accommodating missing values from either table.

The Solution: Using SQL UNION

To achieve the desired result, you will utilize the SQL UNION operator. Here’s how you can do this:

Step 1: Select Data from Table 1

To pull data from Table 1, you will select all relevant columns and use NULL as a placeholder for missing columns from Table 2.

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

Step 2: Select Data from Table 2

Next, you will select the relevant columns from Table 2, using NULL for the columns unique to Table 1.

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

Full Query

By combining these two parts, your final SQL query will look like this:

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

Key Points:

Use NULL for Missing Columns: This will ensure that when joining tables with different structures, you maintain a level of organization by filling in the gaps.

Use UNION ALL: If you wish to include duplicate records from either table, UNION ALL is the way to go. This is crucial for preserving all data entries in your final output.

Conclusion: Mastering SQL Table Joins

Combining two tables with both like and unlike columns can seem challenging at first, but with the right approach using the SQL UNION operator, it's simpler than it seems. Follow these steps, and soon you'll be navigating your databases with ease, ensuring that your data queries yield comprehensive results that serve your analysis needs.

Feel free to reach out in the comments if you have any questions or further challenges regarding SQL queries!

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