Need advice on SQL philosophy - sql

Question

Before I go asking more questions about the coding, I'd like to first figure out the best method for me to follow for making my database. I'm running into a problem with how I should go about structuring it to keep everything minimized and due to its' nature I have lots of re-occurring data that I have to represent.
I design custom shirts and have a variety of different types of shirts for people to choose from that are available in both adult and child sizes of both genders. For example, I have crewneck shirts, raglan sleeves, ringer sleeves and hoodies which are available for men, women, boys, girls and toddlers. The prices are the same for each shirt from the toddler sizes up to 1x in the adult sizes, then 2x, 3x, 4x and 5x are each different prices. Then there's the color options for each kind of shirt which varies, some may have 4 color options, some have 32.
So lets take just the crewneck shirts for an example. Men s-1x, Women s-1x, Boys xs-1x, girls xs-1x and toddlers NB-18months is a total of 22 rows that will be represented in the table and are all the same price. 2X and up only apply to men and women so that's 8 more rows which makes 30 rows total for just the crewneck shirts. When it gets into the color options, there's 32 different colors available for them. If I were to do each and every size for all of them that would be 960 total rows just for the crewneck shirts alone with mainly HIGHLY repeated data for just one minor change.
I thought about it and figured It's best to treat these items on the table as actual items in a stock room because THEY'RE REALLY THERE in the stock room... you don't have just one box of shirts that you can punch a button on the side to turn to any size of color, you have to deal with the actual shirt and tedious task of putting them somewhere, so I deciding against trying to get outrageous with a bunch of foreign keys and indexes, besides that it gets just as tedious and you wind up having to represent just as much but with a lot more tables when you could've just put the data it's linking to in the first table.
If we take just the other 3 kinds of shirts and apply that same logic with all the colors and sizes just for those 4 shirts alone there will be 3,840 rows, with the other shirts left I'm not counting in you could say I'm looking at roughly 10,000 rows of data all in one table. This data will be growing over time and I'm wondering what it might turn into trying to keep it all organized. So I figured maybe the best logic to go with would be to break it down like the do in an actual retail store, which is to separate the departments into men, women, boys, girls and babies. so that way I have 5 separate tables that are only called when the user decides to "go to that department" so if there's a man who wants the men shirts he doesn't have 7,000+ rows of extra data present that doesn't even apply to what he's looking for.
Would this be a better way of setting it up? or would it be better to keep it all as one gigantic table and just query the "men" shirts in the php from the table in the section for men and the same with women and kids?
My next issue is all the color options that may be available, as I said before some shirts will have as few as 4 some will have as many as 32, so some of those are enough data to form a table all on their own, so I could really have a separate table for every kind of shirt. I'll be using a query in php to populate my items from the tables so I don't have to code so much in the html and javascript. That way I can set it to SELECT ALL * table WHERE type=men and it will take all the men shirts and auto populate the coding for each one. That way as I add and take things to and from the tables it'll automatically be updated. I already have an idea for HOW I'm going to do that, but I can only think so far into it because I haven't decided on a good way to set the tables up which is what I'd have to structure it to call from.
For example, if I have all the color options of each shirt all on the same table versus having it broken down and foreign keys linking to other tables to represent them. that would be two totally different ways of having to call it forth, so I'm stuck on this and don't really know where to go with it. any suggestions?

Answer 1

Typically retail organization is by SKU (stock keeping unit). Department and color are attributes of a garment, not the way you identify the garment for the purpose of accounting or stocking.
CREATE TABLE Skus (
sku BIGINT UNSIGNED PRIMARY KEY,
description TEXT,
department VARCHAR(10) NOT NULL,
color VARCHAR(10) NOT NULL,
qty_in_stock INT UNSIGNED NOT NULL DEFAULT 0,
unit_price NUMERIC(9,2) NOT NULL,
FOREIGN KEY (department) REFERENCES Departments(department),
FOREIGN KEY (color) REFERENCES Colors(color)
);
This is better than splitting into five tables, because:
You can quickly get a sum of the total value of all your stock.
You can switch the department of a given SKU easily.
When someone buys a few garments, their order lineitems reference a single table instead of five different tables (that would be invalid for a relational database).
There are lots of other examples of tasks that are easier if similar entities are stored in one table.

Answer 2

I know you don't want to break it out into separate tables, but I think going the multiple table route would be the best. However, I don't think it is as bad as you think. My suggestion would be the following. Obviously, you want to change the names of the fields, but this is a quick representation:
Shirts
- id (primary key)
- description
- men (Y/N)
- women (Y/N)
- boy (Y/N)
- girl (Y/N)
- toddlers (Y/N)
Sizes
- id (primary key)
- shirt_id (foreign key)
- Size
Colors
- id (primary key)
- shirt_id (foreign key)
- Color
Price
- id (primary key)
- shirt_id (foreign key)
- size_id (foreign key)
- price
Having these three tables makes it so that you won't have to store all 10,000 rows in one single table and maintain it, but the data is still all there. Keeping your data separated into their proper places keeps from replicating needless information.
Want to pull all men's shirts?
SELECT * FROM shirts WHERE men = '1'
To be honest, you should really have at least 5 or 6 tables. One/two containing the labels for sizes and colors (either one table containing all, or one for each one) and the other 4 containing the actual data. This will keep your data uniform across everything (example: Blue vs blue). You know what they say, there is more than one way to skin a cat.

Answer 3

You need to think about a database term called 'normalization'. Normalization means that everything has it's place in the database and should not be listed twice but reused as needed. The most common mistake people make is to not ask or think about what will happen down the road and they put up a database that has next to no normalization, has massive memory consumed do to large datatypes, no seeding done, and is completely inflexible and comes at a great cost to change later because it was made without thinking of the future.
There are many levels of normalization but the most consistent thing is to think about a simple example I could give you to explain some simple concepts that can be applied to larger things later. This is assuming you have access to SQL management studio, SSMS, HOWEVER if you are using MYSQL or Oracle the principles are still very similar and the comments sections will show what I am getting at. This example you can self run if you have SSMS and just paste it in and hit F5. If you don't just look at the comments section although these concepts are better to see in action than to try to just envision what they mean.
Declare #Everything table (PersonID int, OrderID int, PersonName varchar(8), OrderName varchar(8) );
insert into #Everything values (1, 1, 'Brett', 'Hat'),(1, 2, 'Brett', 'Shirt'),(1, 3, 'Brett', 'Shoes'),(2,1,'John','Shirt'),(2,2,'John','Shoes');
-- very basic normalization level in that I did not even ATTEMPT to seperate entities into different tables for reuse.
-- I just insert EVERYTHING as I get in one place. This is great for just getting off the ground or testing things.
-- but in the future you won't be able to change this easily as everything is here and if there is a lot of data it is hard
-- to move it. When you insert if you keep adding more and more and more columns it will get slower as it requires memory
-- for the rows and the columns
Select Top 10 * from #Everything
declare #Person table ( PersonID int identity, PersonName varchar(8));
insert into #Person values ('Brett'),('John');
declare #Orders table ( OrderID int identity, PersonID int, OrderName varchar(8));
insert into #Orders values (1, 'Hat'),(1,'Shirt'),(1, 'Shoes'),(2,'Shirt'),(2, 'Shoes');
-- I now have tables storing two logic things in two logical places. If I want to relate them I can use the TSQL language
-- to do so. I am now using less memory for storage of the individual tables and if one or another becomes too large I can
-- deal with them isolated. I also have a seeding record (an ever increasing number) that I could use as a primary key to
-- relate row position and for faster indexing
Select *
from #Person p
join #Orders o on p.PersonID = o.PersonID
declare #TypeOfOrder table ( OrderTypeID int identity, OrderType varchar(8));
insert into #TypeOfOrder values ('Hat'),('Shirt'),('Shoes')
declare #OrderBridge table ( OrderID int identity, PersonID int, OrderType int)
insert into #OrderBridge values (1, 1),(1,2),(1,3),(2,2),(2,3);
-- Wow I have a lot more columns but my ability to expand is now pretty flexible I could add even MORE products to the bridge table
-- or other tables I have not even thought of yet. Now that I have a bridge table I have to list a product type ONLY once ever and
-- then when someone orders it again I just label the bridge to relate a person to an order, hence the name bridge as it on it's own
-- serves nothing but relating two different things to each other. This method takes more time to set up but in the end you need
-- less rows of your database overall as you are REUSING data efficiently and effectively.
Select Top 10 *
from #Person p
join #OrderBridge o on p.PersonID = o.PersonID
join #TypeOfOrder t on o.OrderType = t.OrderTypeID