Although one can certainly write an entire book on relational databases, and another on SQL, the essentials of these technologies are not hard to understand. A database is a repository of data. A relational database organizes your data into tables. Consider the Northwind database provided with Microsoft SQL Server 7, SQL Server 2000, and all versions of Microsoft Access.
14.1.1 Tables, Records, and Columns
The Northwind database describes a fictional company buying and selling food products. The data for Northwind is divided into 13 tables, including Customers, Employees, Orders, Order Details, Products, and so forth.
Every table in a relational database is organized into rows, where each row represents a single record. The rows are organized into columns. All the rows in a table have the same column structure. For example, the Orders table has these columns: OrderID, CustomerID, EmployeeID, OrderDate, etc.
For any given order, you need to know the customer's name, address, contact name, and so forth. You could store that information with each order, but that would be very inefficient. Instead, we use a second table called Customers, in which each row represents a single customer. In the Customers table is a column for the CustomerID. Each customer has a unique ID, and that field is marked as the primary key for that table. A primary key is the column or combination of columns that uniquely identifies a record in a given table.
The Orders table uses the CustomerID as a foreign key. A foreign key is a column (or combination of columns) that is a primary (or otherwise unique) key from a different table. The Orders table uses the CustomerID (the primary key used in the Customers table) to identify which customer has placed the order. To determine the address for the order, you can use the CustomerID to look up the customer record in the Customers table.
This use of foreign keys is particularly helpful in representing one-to-many or many-to-one relationships between tables. By separating information into tables that are linked by foreign keys, you avoid having to repeat information in records. A single customer, for example, can have multiple orders, but it is inefficient to place the same customer information (name, phone number, credit limit, and so on) in every order record. The process of removing redundant information from your records and shifting it to separate tables is called normalization.
Normalization not only makes your use of the database more efficient, but also it reduces the likelihood of data corruption. If you kept the customer's name both in the Customers table and also in the Orders table, you would run the risk that a change in one table might not be reflected in the other. Thus, if you changed the customer's address in the Customers table, that change might not be reflected in every row in the Orders table (and a lot of work would be necessary to make sure that it was reflected). By keeping only the CustomerID in Orders, you are free to change the address in Customers, and the change is automatically reflected for each order.
Just as C# programmers want the compiler to catch bugs at compile time rather than at runtime, database programmers want the database to help them avoid data corruption. The compiler helps avoid bugs in C# by enforcing the rules of the language (for example, you can't use a variable you've not defined). SQL Server and other modern relational databases avoid bugs by enforcing constraints that you request. For example, the Customers database marks the CustomerID as a primary key. This creates a primary key constraint in the database, which ensures that each CustomerID is unique. If you were to enter a customer named Liberty Associates, Inc. with the CustomerID of LIBE, and then tried to add Liberty Mutual Funds with a CustomerID of LIBE, the database would reject the second record because of the primary key constraint.
14.1.3 Declarative Referential Integrity
Relational databases use Declarative Referential Integrity (DRI) to establish constraints on the relationships among the various tables. For example, you might declare a constraint on the Orders table that dictates that no order can have a CustomerID unless that CustomerID represents a valid record in Customers. This helps avoid two types of mistakes. First, you cannot enter a record with an invalid CustomerID. Second, you cannot delete a Customer record if that CustomerID is used in any order. The integrity of your data and their relationships are thus protected.
The most popular language for querying and manipulating databases is SQL, usually pronounced "sequel." SQL is a declarative language, as opposed to a procedural language, and it can take a while to get used to working with a declarative language when you are used to languages such as C#.
The heart of SQL is the query. A query is a statement that returns a set of records from the database.
For example, you might like to see all the CompanyNames and CustomerIDs of every record in the Customers table in which the customer's address is in London. To do so, write:
Select CustomerID, CompanyName from Customers where city = 'London'
This returns the following six records as output:
CustomerID CompanyName ---------- ---------------------------------------- AROUT Around the Horn BSBEV B's Beverages CONSH Consolidated Holdings EASTC Eastern Connection NORTS North/South SEVES Seven Seas Imports
SQL is capable of much more powerful queries. For example, suppose the Northwinds manager would like to know what products were purchased in July of 1996 by the customer "Vins et alcools Chevalier." This turns out to be somewhat complicated. The Order Details table knows the ProductID for all the products in any given order. The Orders table knows which CustomerIDs are associated with an order. The Customers table knows the CustomerID for a customer, and the Products table knows the Product name for the ProductID. How do you tie all this together? Here's the query:
select o.OrderID, productName from [Order Details] od join orders o on o.OrderID = od.OrderID join products p on p.ProductID = od.ProductID join customers c on o.CustomerID = c.CustomerID where c.CompanyName = 'Vins et alcools Chevalier' and orderDate >= '7/1/1996' and orderDate <= '7/31/1996'
This asks the database to get the OrderID and the product name from the relevant tables. First, look at Order Details (which we've called od for short), then join that with the Orders table for every record in which the OrderID in the Order Details table is the same as the OrderID in the Orders table.
When you join two tables, you can say either "Get every record that exists in either table" (this is called an outer join), or you can say, as I've done here, "Get only those records that exist in both tables" (called an inner join). That is, an inner join states to get only the records in Orders that match the records in Order Details by having the same value in the OrderID field (on o.Orderid = od.Orderid).
The SQL statement goes on to ask the database to create an inner join with Products, getting every row in which the ProductID in the Products table is the same as the ProductID in the Order Details table.
Then create an inner join with customers for those rows where the CustomerID is the same in both the Orders table and the Customer table.
Finally, tell the database to constrain the results to only those rows in which the CompanyName is the one you want, and the dates are in July.
The collection of constraints finds only three records that match:
OrderID ProductName ----------- ---------------------------------------- 10248 Queso Cabrales 10248 Singaporean Hokkien Fried Mee 10248 Mozzarella di Giovanni
This output shows that there was only one order (10248) in which the customer had the right ID and in which the date of the order was July 1996. That order produced three records in the Order Details table, and using the product IDs in these three records, you got the product names from the Products table.
You can use SQL not only for searching for and retrieving data, but also for creating, updating, and deleting tables, and generally managing and manipulating both the content and the structure of the database.
For a full explanation of SQL and tips on how to put it to best use, I recommend Transact SQL Programming, by Kline, Gould, and Zanevsky (O'Reilly).