Adding New Columns and Variable Rows to SQL Select Query as Output: Performing Arithmetic Operations in it

Introduction

In this article, we will explore how to add new columns and variable rows to a SQL select query as output. We will also discuss performing arithmetic operations on these newly added columns. To achieve this, we will use the SELECT statement with the SELECT DISTINCT clause, which allows us to specify multiple columns in our query.

Understanding the Problem

The problem presented is as follows: you are writing a SQL query for selecting data from a table and want to add new columns (PERIOD_TYPE) that contain specific dates based on certain criteria. You also need to perform arithmetic operations on these newly added columns to calculate sums of sales data.

The given code snippet demonstrates the attempt to accomplish this task using a combination of DECLARE statements, SET statements, and SELECT statements.

Breaking Down the Problem

To break down the problem into manageable parts, let’s analyze each section:

Declaring Variables
- The first step is to declare variables that will hold values used in the query.
- In this case, we have several variables declared: @date, @sale_date_ly, @date_using, and others.
Setting Variable Values
- Next, we set the values of these variables using SET statements.
SELECT Statement
- The main part of our query is a SELECT statement that joins two tables (or shapes) using the SELECT DISTINCT clause.

Solving the Problem

To solve this problem, let’s break down each step:

Step 1: Calculate Period Type Columns

First, we need to calculate the period type columns (@DAY_PERIOD_TYPE_TY, @WTD_PERIOD_TYPE_TY, @MTD_PERIOD_TYPE_TY, and @YTD_PERIOD_TYPE_TY). We can do this by using a combination of functions available in SQL Server.

Calculating Period Type Columns

-- Calculate DAY period type
SELECT @DAY_PERIOD_TYPE_TY = DATE FROM [dbo].[DimDate] WHERE date = @date_using

-- Calculate WTD period type
SELECT @WTD_PERIOD_TYPE_TY = CONCAT(Convert(date,DATEADD(wk,DATEDIFF(wk,0,@date_using),0)), ' To ', @date_using )

-- Calculate MTD period type
SELECT @MTD_PERIOD_TYPE_TY = CONCAT ((select FirstDayOfMonth from [dbo].[DimDate] where date=@date_using ), ' To ', @date_using )

-- Calculate YTD period type
SELECT @YTD_PERIOD_TYPE_TY = CONCAT ((select FirstDayOfYear from [dbo].[DimDate] where date=@date_using ), ' To ', @date_using )

Step 2: Join Tables

Next, we join the tables using a combination of SELECT DISTINCT clause and inner joins.

Joining Tables

-- Join tables
SELECT  
A.COUNTRY As COUNTRY,
@sale_date_ly As PERIOD_TYPE ,
sum(B.TY_SALES)  AS SALES_LY_USD

from [SE].[SHAPE] A
INNER JOIN [SE].[LF_SHAPE] B
ON A.COUNTRY=B.COUNTRY

Step 3: Perform Arithmetic Operations

Finally, we perform arithmetic operations on the newly added columns to calculate sums of sales data.

Performing Arithmetic Operations

-- Perform arithmetic operations
SELECT  
A.COUNTRY As COUNTRY,
@sale_date_ly As PERIOD_TYPE ,
sum(B.TY_SALES)  AS SALES_LY_USD

Conclusion

In this article, we explored how to add new columns and variable rows to a SQL select query as output. We also discussed performing arithmetic operations on these newly added columns. To achieve this, we used the SELECT statement with the SELECT DISTINCT clause, which allows us to specify multiple columns in our query.

By breaking down each step of the problem into manageable parts, we were able to solve the issue presented in the question. We hope that this article has been helpful in understanding how to accomplish similar tasks using SQL Server.

Example Use Case

Here is an example use case for the solution provided:

Suppose you are working with a sales database and want to generate reports on sales by day, week, month, or year. You can use the SELECT statement with the SELECT DISTINCT clause to specify multiple columns in your query.

For instance, if you have a table called Sales that contains sales data for different dates, you can use the following SQL query:

-- Select all columns from Sales table
SELECT  
S.COUNTRY As COUNTRY,
S.SALE_DATE As SALE_DATE ,
sum(S.TY_SALES)  AS SALES_LY_USD

from [SE].[SHAPE] S
INNER JOIN [SE].[LF_SHAPE] SS
ON S.COUNTRY=SS.COUNTRY
WHERE S.SALE_DATE BETWEEN @start_date AND @end_date

-- Perform arithmetic operations on newly added columns
SELECT  
S.COUNTRY As COUNTRY,
@sale_date_ly As PERIOD_TYPE ,
sum(S.TY_SALES)  AS SALES_LY_USD

In this example, we use the SELECT statement with the SELECT DISTINCT clause to specify multiple columns in our query. We also perform arithmetic operations on the newly added columns to calculate sums of sales data.

By using this approach, you can generate reports on sales by day, week, month, or year and perform arithmetic operations on these columns to calculate sums of sales data.

Last modified on 2023-09-09