I’ve created my table. I’m trying to craate a query that multiply and add sold_quantity from sold table and sale_price from on_sale table and called it R1 for now, and retail_price from product table and sold_quantity from sold table called it R2 for now.
In my query, I want to calculate my revenue. The catch is there’s two different date but one sale quantity. That means it’s kinda hard for me to distinguish twO types of sales( discounted sale, retail sale).
For example, on Feb.1st, I have a sale going on, I sold 10 quantity, and price sold is as sale_price and date is saved as sale_date, refer to On_sale table. On Feb.2, I sold 8 quantity , but price sold is saved as retail_price and saved as sold_date.
CREATE TABLE Sold ( store_number int(16) NOT NULL AUTO_INCREMENT, pid int(16) NOT NULL, sold_date date NOT NULL, sold_quantity int(16) NOT NULL, PRIMARY KEY (pid,store_number,sold_date) ); CREATE TABLE Store ( store_number int(16) NOT NULL AUTO_INCREMENT, phone_number varchar(16) NOT NULL DEFAULT '0', street_address varchar(250) NOT NULL, city_name varchar(250) NOT NULL, state varchar(250) NOT NULL, PRIMARY KEY (store_number) ); CREATE TABLE On_sale ( pid int(16) NOT NULL, sale_date date NOT NULL, sale_price float(16) NOT NULL, PRIMARY KEY (pid,sale_date) ); CREATE TABLE Product ( pid int(16) NOT NULL, product_name varchar(250) NOT NULL, retail_price float(16) NOT NULL, manufacture_name varchar(250) NOT NULL, PRIMARY KEY (pid) ); CREATE TABLE City ( city_name varchar(250) NOT NULL, state varchar(250) NOT NULL, population int(16) NOT NULL DEFAULT '0', PRIMARY KEY (city_name,state) );
This is what I want
SAMPLE DATA
STORE TABLES store_number phone_number street_address city_name state 1 # ### New York NY 2 # ### HOUSTON TX 3 # ### L.A CA Sold Tables store_number PID SOLD DATE SOLD_QUANTITY 1 1 2/2/2017 3 2 2 2/3/2018 3 3 3 2/5/2019 4 On_sale Tables PID SALE_DATE SALE PRICE 1 2/4/2018 2 Product Tables PID PRODUCT NAME RETAIL_PRICE manufacture_name 1 XX 5 XXX 2 XX 4 XXX 3 XX 3 XXX CITY TABLE CITY_NAME STATE POPULATION New York NY 100 HOUSTON TX 200 L.A CA 201 RESULT YEAR REVENUE POPULATION 2017 15 (NEW YORK)SMALL 2018 14 (HOUSTON)MEDIUM 2019 12 (L.A) LARGE
Explanation of my data
:
This is very confusing. First I need to display year based on sold date and sale date, then calculate revenue. For example,in year 2018, the revneue is (2 from on_sale table’s sale_price) + (12 (3 * 4, 3 is the sold_quantity from sold_table, and 4 is retail_price) = 14.
The city size is separated by ranges, where 0>#<100 is small 100>=x<200 is medium and anything above 200 is large. the city name in the parenthesis is just to help track. The city is based on the city name and state in store table, and that is doen by comparing store_number on both sold table and store table
This requires me to join city table after querying to get R1(normal price) and R2(on sale price). Here’s what I got. I’m very lost
SELECT Sold.sold_quantity, Product.retail_price AS S1 SUM(Product.retail_price*Sold.sold_quantity) AS R1 FROM Sold LEFT JOIN Product ON Sold.pid=Product.pid SELECT Sold.sold_quantity, On_sale.sale_price AS S2 SUM(On_sale.sale_price) AS R2 FROM Sold LEFT JOIN On_sale ON Sold.pid=On_sale.pid
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Answer
I don’t understand the use of LEFT JOIN
in your queries. You seem to have a well-defined data model and the ids should line up.
You specifically say that you want to add R1
and R2
, so the query you describe looks like this:
SELECT year(s.sold_date) as yr, c.population, (SUM(p.retail_price * s.sold_quantity) + SUM(os.sale_price * s.sold_quantity) ) AS revenue FROM Sold s JOIN Product p ON s.pid = p.pid JOIN city c ON c.city_name = p.manufacture_name LEFT JOIN On_sale os ON s.pid = os.pid AND os.sale_date = s.sold_date GROUP BY year(s.sold_date), c.population ORDER BY year(s.sold_date), c.population;
Note that this adds an extra condition saying that the dates match for the on_sale
table. That makes sense to me.
Adding these two revenue numbers seems very suspicious to me. I would expect that you would want the sales price, if it exists, and otherwise the retail price. If so then the calculation would be:
SUM(COALESCE(os.sale_price, p.retail_price) * s.sold_quantity) AS revenue
If you want the sum of the discount amounts, then the difference makes sense.