Conditional Aggregation in SQL: Calculating Average Based on Conditions

Introduction

Conditional aggregation is a powerful feature in SQL that allows you to perform calculations based on specific conditions. In this article, we will explore how to use conditional aggregation to calculate the average value of a column while meeting certain conditions.

We will start by examining the problem statement and then dive into the solution using an example table and SQL query.

Problem Statement

You have a table with several columns including Id, Value, Code, and Date. You want to calculate the average value of Value for records where the maximum date for each Id is greater than or equal to the current year minus 1, and you also want to ensure that there are values present in the Value column for at least 3 years.

Example Table

Here’s an example table to illustrate this problem:

Query without Conditions

The original query provided calculates the average value of Value for each row while considering a window of 2 preceding and current rows. However, it does not meet our conditions as specified.

SELECT Id,
       AVG(Value) OVER(partition by ID Order by [date] rows between 2 preceding and current row) as avg_value,
FROM [table]
WHERE Code = 'SLS'

This query will return the average value for each Id, but it does not consider the conditions specified in the problem statement.

Solution

To meet our conditions, we can use conditional aggregation. We’ll break down the solution into two parts: calculating the maximum date and ensuring there are values present for at least 3 years.

Part 1: Calculating Maximum Date

We want to calculate the maximum date for each Id. This can be done using the MAX function with the ROW_NUMBER() window function.

SELECT Id,
       MAX(date) as max_date
FROM [table]
WHERE Code = 'SLS'
GROUP BY Id

However, this query does not consider our condition of only calculating for the maximum date greater than or equal to the current year minus 1. We can use a CASE statement within our final query to achieve this.

SELECT Id,
       AVG(CASE WHEN date > dateadd(year, -1, getdate()) THEN Value END)
           OVER (partition by ID
                 order by [date] rows
                 between 2 preceding and current row
                ) as avg_value
FROM [table]
WHERE Code = 'SLS'

In this query, getdate() returns the current date. We compare it to the date minus 1 year using dateadd(year, -1, getdate()). If the date is greater than this value, we include its corresponding value in our average calculation.

Part 2: Ensuring Values for at Least 3 Years

To ensure that there are values present in the Value column for at least 3 years, we can use another window function, such as COUNT() with a filter clause. However, this approach is less efficient and may not accurately model your requirements.

A better approach would be to calculate the total count of rows per Id within each year, then ensure that the total count for at least 3 years is greater than zero.

SELECT Id,
       AVG(CASE WHEN date > dateadd(year, -1, getdate()) THEN Value END)
           OVER (partition by ID
                 order by [date] rows
                 between 2 preceding and current row
                ) as avg_value
FROM [table]
WHERE Code = 'SLS' AND
       (SELECT COUNT(*) 
        FROM [table] t2
        WHERE t2.Id = Id AND t2.date BETWEEN dateadd(year, -3, getdate()) AND getdate()
       ) > 0

In this query, we calculate the count of rows within each year using a subquery and check if it is greater than zero. This ensures that there are values present in the Value column for at least 3 years.

Conclusion

Conditional aggregation provides an efficient way to perform calculations based on specific conditions. In this article, we demonstrated how to use conditional aggregation to calculate the average value of a column while meeting certain conditions. We covered calculating the maximum date and ensuring that there are values present in the Value column for at least 3 years.

Additional Notes

• The provided solution assumes that you’re using SQL Server as your database management system.
• If you’re using a different database management system, such as MySQL or PostgreSQL, the syntax may vary.
• Always test and verify the results of your queries to ensure they meet your requirements.

Last modified on 2024-11-29