Understanding Growth Rate Queries in SQL

In this article, we will delve into the world of growth rate queries in SQL. We will explore how to write a query that calculates the cumulative sum of products for each company by month, and provide an example using a Hugo-powered website.

Introduction

A growth rate query is used to calculate the change in sales or revenue over time. In this article, we will focus on calculating the cumulative sum of products for each company by month. This type of query is commonly used in business intelligence and data analysis to understand trends and patterns in sales data.

Understanding the Problem

The problem presented in the question describes a scenario where a company has different counts of products for each month. The goal is to calculate the cumulative sum of these counts for each company by month. For example, if a company had 4 products last month and 1 product this month, we want to show the 4 counts for the last month and add last month’s counts to this month’s count.

Querying the Data

To solve this problem, we need to query the data using SQL. We will start by selecting all columns from the Product table and joining it with the Company table on the ManufacturerID column.

SELECT * FROM (SELECT c.Name,YEAR(p.DateAdded) [Year], 
              DATENAME(MONTH, p.DateAdded) [Month], 
              COUNT(ProductID)
              --+lag(COUNT(p.ProductID),1) OVER ( ORDER BY YEAR(p.DateAdded),DATENAME(MONTH, p.DateAdded)) 
              ProductCount
            FROM Product.Product p
            LEFT JOIN (SELECT ID,name from sourcing.Company WHERE CompanyTypeID=1 AND DateDeleted IS null) c ON p.ManufacturerID=c.id
            WHERE p.DateArchived IS NULL AND p.ManufacturerID=571 AND YEAR(p.DateAdded) IN ('2015')
            GROUP BY c.Name,YEAR(p.DateAdded), 
                      DATENAME(MONTH, p.DateAdded)) AS MontlySalesData ORDER BY MontlySalesData.Year,MontlySalesData.Month

Using a Common Table Expression (CTE)

The query provided in the question uses a common table expression (CTE) to solve the problem. A CTE is a temporary result set that can be referenced within a SELECT, INSERT, UPDATE, or DELETE statement.

WITH cte as (
  select *, row_number() over( order by (SELECT NULL)) as rn
  from mytable
)

In this example, we create a CTE called cte and use the row_number() function to assign a unique number to each row. This allows us to reference the previous row in the query.

select Companies, Year, Month, sum(ProductCOunt) over (partition by Companies ORDER BY rn ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as ProductCOunt
from cte;

In this final step, we select the Companies, Year, and Month columns from the CTE, and calculate the cumulative sum of ProductCOunt using the over() function.

Results

The query provided in the question produces the following results:

However, the expected results are different. The expected results should show the cumulative sum of products for each company by month.

Expected Results

The expected results should show the cumulative sum of products for each company by month. For example, if a company had 4 products last month and 1 product this month, we want to show the 4 counts for the last month and add last month’s counts to this month’s count.

Companies   Year    Month   ProductCOunt
Company1    2022    January     5
Company1    2022    February    11
Company2    2022    January     5
Company2    2022    February    11
Company3    2022    January     5
Company3    2022    February    11

However, the provided results do not match the expected results. To achieve the expected results, we need to modify the query to use a cumulative sum.

WITH cte as (
  select *, row_number() over( order by (SELECT NULL)) as rn
  from mytable
)
select Companies, Year, Month, 
       SUM(ProductCOunt) OVER (PARTITION BY Companies ORDER BY rn ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as ProductCOunt
from cte;

In this modified query, we use the SUM() function with an over() clause to calculate the cumulative sum of products for each company by month.

Conclusion

In this article, we explored how to write a growth rate query in SQL. We used a common table expression (CTE) and the row_number() function to assign a unique number to each row. We then used the SUM() function with an over() clause to calculate the cumulative sum of products for each company by month.

However, the provided results did not match the expected results. To achieve the expected results, we need to modify the query to use a cumulative sum.

Example Use Cases

This type of query can be used in various scenarios where you need to analyze sales data over time. For example:

• Analyzing sales trends for different products or categories
• Calculating revenue growth for specific companies or industries
• Identifying seasonal fluctuations in sales
• Comparing sales performance between different regions or countries

Code Snippets

Here is a code snippet that demonstrates how to use the row_number() function with an over() clause to calculate the cumulative sum of products:

WITH cte as (
  select *, row_number() over( order by (SELECT NULL)) as rn
  from mytable
)
select Companies, Year, Month, 
       SUM(ProductCOunt) OVER (PARTITION BY Companies ORDER BY rn ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as ProductCOunt
from cte;

This code snippet uses a CTE to assign a unique number to each row in the mytable table. It then uses the SUM() function with an over() clause to calculate the cumulative sum of products for each company by month.

References

• “Common Table Expressions (CTEs)” - SQL Server Documentation
• “ROW_NUMBER() Function” - Oracle Documentation
• “SUM() Function” - MySQL Documentation

Last modified on 2025-01-24