Understanding Union with Group By: A Deeper Dive into SQL Queries

In this article, we will delve into the concept of union with group by in SQL queries. We’ll explore how to combine data from multiple tables using a union operator and then group the results based on certain conditions.

Introduction to Union

The union operator is used to combine the result sets of two or more SELECT statements. It returns all rows from both queries, excluding any duplicates. However, when dealing with grouped queries, things can get complicated quickly. In this article, we’ll explore how to use union with group by to combine data from multiple tables and then group the results.

Understanding Group By

Grouping is a way of aggregating data in SQL. It allows us to perform calculations on groups of rows that share common characteristics. The basic syntax for grouping is as follows:

SELECT column1, column2, ...
FROM table_name
GROUP BY column1, column2, ...

Union with Group By

Now, let’s talk about combining data from multiple tables using union and then grouping the results.

Suppose we have three tables: Products, Assigns, and Legacies. We want to combine data from these tables using union and then group the results based on certain conditions. Here’s an example of how we can achieve this:

Step 1: Define the Tables

Let’s define our three tables with some sample data.

-- Create the Products table
CREATE TABLE Products (
    productID INT,
    serviceName VARCHAR(255)
);

-- Insert some sample data into the Products table
INSERT INTO Products (productID, serviceName) VALUES
(1, 'Gold Service'),
(2, 'Silver Service'),
(3, 'Bronze Service');

-- Create the Assigns table
CREATE TABLE Assigns (
    ApplicantID INT,
    serviceID INT,
    status INT
);

-- Insert some sample data into the Assigns table
INSERT INTO Assigns (ApplicantID, serviceID, status) VALUES
(1, 1, 0),
(2, 1, 0),
(3, 1, 1),
(4, 2, 0),
(5, 1, 1);

-- Create the Legacies table
CREATE TABLE Legacies (
    ApplicantID INT,
    serviceID INT,
    status INT
);

-- Insert some sample data into the Legacies table
INSERT INTO Legacies (ApplicantID, serviceID, status) VALUES
(1, 1, 0),
(2, 1, 0),
(3, 1, 0),
(4, 2, 0),
(5, 1, 1);

Step 2: Write the Union Query

Now that we have our tables defined, let’s write a union query to combine data from the Assigns and Legacies tables.

SELECT 
    s.serviceID,
    s.serviceName,
    COUNT(DISTINCT a.ApplicantID) AS FullCount,
    SUM(CASE WHEN a.status = 0 THEN 1 ELSE 0 END) AS WaitingCount,
    SUM(CASE WHEN a.status = 1 THEN 1 ELSE 0 END) AS InProgressCount
FROM 
    (SELECT ApplicantID, serviceID, status FROM Assigns UNION ALL SELECT ApplicantID, serviceID, status FROM Legacies) t
LEFT JOIN Products s ON s.productID = t.serviceID
WHERE (
    s.clientID = @ClientID 
    OR LAG(s.clientID, 1, NULL) OVER (ORDER BY s.productID) = @CompanyName
)
GROUP BY 
    s.serviceID,
    s.serviceName;

Step 3: Group the Results

Now that we have combined data from our tables using union, let’s group the results based on certain conditions.

As you can see from the query above, we’re grouping by both serviceID and serviceName. We’re also applying a condition to filter out rows where clientID or client is not equal to @ClientID or @CompanyName.

Explanation

In this example, we’ve combined data from the Assigns and Legacies tables using union. We’ve then grouped the results based on both serviceID and serviceName. Finally, we’re applying a condition to filter out rows where clientID or client is not equal to @ClientID or @CompanyName.

The key to understanding this query lies in recognizing how to combine data from multiple tables using union. We’ve also applied the grouping clause to aggregate data based on certain conditions.

Conclusion

In conclusion, union with group by can be a powerful tool for combining data from multiple tables and then applying certain conditions to filter out rows. By applying the union operator followed by a group by clause, we can combine data from different sources and perform calculations on groups of rows that share common characteristics.

This article has explored how to use union with group by in SQL queries. We’ve covered the basics of union and grouping and applied these concepts to a real-world example.

Last modified on 2024-07-26