relational-database

Im working on a project. Its mostly for learning purposes, i find actually trying a complicated project is the best way to learn a language after grasping the basics. Database design is not a strong point, i started reading up on it but its early days and im still learning. Here is my alpha schema, im really at the point where im just trying to jot down everything i can think of and seeing if any issues jump out. http://diagrams.seaquail.net/Diagram.aspx?ID=10094# Some of my concerns i would like feedback on: Notice for the core attributes like area for example, lets say for simplicity the

I'm new to databases and I've never worked with any RDBMS. However I get the basic idea of relational databases. At least I think I do ;-) Let's say I have a user database with the following properties for each user: user id name zip city In a relational database I would for example model it in a table called user user id name location_id and have a second table called location location id zip city And location_id is a foreign key (reference) to an entry in the location table. If I understand it right the advantage is here, if the zip code for a certain city changes I only have to change

Looking to figure out the proper way to model the below requirements. There are 3 types of “parties” to be concerned with, a Fan, a Band, and a BandMember. That BandMember will always be associated with a Band and can also be a Fan of any band. There are common attributes between a Fan, a Band, and a BandMember, but each of these 3 will also have their own unique attributes. A Fan can be a fan of of any Band or none at all This is a small part of a bigger thought but it is creating confusion in expanding the model. I believe it would have to be diagram 2 or some other option since I don't see

What is the best way to store user relationships, e.g. friendships, that must be bidirectional (you're my friend, thus I'm your friend) in a rel. database, e.g. MYSql? I can think of two ways: Everytime a user friends another user, I'd add two rows to a database, row A consisting of the user id of the innitiating user followed by the UID of the accepting user in the next column. Row B would be the reverse. You'd only add one row, UID(initiating user) followed by UID(accepting user); and then just search through both columns when trying to figure out whether user 1 is a friend of user 2. Surely

I find it very common to want to model relational data in my functional programs. For example, when developing a web-site I may want to have the following data structure to store info about my users: data User = User { name :: String , birthDate :: Date } Next, I want to store data about the messages users post on my site: data Message = Message { user :: User , timestamp :: Date , content :: String } There are multiple problems associated with this data structure: We don't have any way of distinguishing users with similar names and birth dates. The user data will be duplicated on

Is it that a primary key is the selected candidate key chosen for a given table? Candidate Key – A Candidate Key can be any column or a combination of columns that can qualify as unique key in database . There can be multiple Candidate Keys in one table. Each Candidate Key can qualify as Primary Key. Primary Key – A Primary Key is a column or a combination of columns that uniquely identify a record . Only one Candidate Key can be Primary Key. More on this link with example John Woo's answer is correct, as far as it goes. Here are a few additional points. A primary key is always one of the

I'm trying to learn about OLAP and data warehousing, and I'm confused about the difference between relational and dimensional modeling. Is dimensional modeling basically relational modeling, but allowing for redundant/un-normalized data? For example, let's say I have historical sales data on (product, city, # sales). I understand that the following would be a relational point-of-view: Product | City | # Sales Apples, San Francisco, 400 Apples, Boston, 700 Apples, Seattle, 600 Oranges, San Francisco, 550 Oranges, Boston, 500 Oranges, Seattle, 600 While the following is a more dimensional point