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A Quick Tour of SQL
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efore diving into the details of SQL, it s a good idea to develop an overall perspective on the language and how it works. This chapter contains a quick tour of SQL that illustrates its major features and functions. The goal of the quick tour is not to make you proficient in writing SQL statements; that is the goal of Part II of this book. Rather, by the time you ve finished this chapter, you will have a basic familiarity with the SQL language and an overview of its capabilities.
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The examples in the quick tour are based on a simple relational database for a small distribution company. The database, shown in Figure 2-1, stores the information
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A simple relational database
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A Quick Tour of SQL
needed to implement a small order processing application. Specifically, it stores the following information: I The customers who buy the company s products I The orders placed by those customers I The salespeople who sell the products to customers I The sales offices where those salespeople work This database, like most others, is a model of the real world. The data stored in the database represents real entities customers, orders, salespeople, and offices. There is a separate table of data for each different kind of entity. Database requests that you make using the SQL language parallel real-world activities, as customers place, cancel, and change orders, as you hire and fire salespeople, and so on. Let s see how you can use SQL to manipulate data.
AN OVERVIEW OF SQL
Retrieving Data
First, let s list the sales offices, showing the city where each one is located and its yearto-date sales. The SQL statement that retrieves data from the database is called SELECT. This SQL statement retrieves the data you want:
SELECT CITY, OFFICE, SALES FROM OFFICES CITY OFFICE SALES ------------ ------- -----------Denver 22 $186,042.00 New York 11 $692,637.00 Chicago 12 $735,042.00 Atlanta 13 $367,911.00 Los Angeles 21 $835,915.00
The SELECT statement asks for three pieces of data the city, the office number, and the amount of sales for each office. It also specifies that all of this data comes from the OFFICES table, which stores data about sales offices. The results of the query appear, in tabular form, immediately after the request. The SELECT statement is used for all SQL queries. For example, here is a query that lists the names and year-to-date sales for each salesperson in the database. It also shows the quota (sales target) and the office number where each person works. In this case, the data comes from the next SALESREPS table.
SQL: The Complete Reference
SELECT NAME, REP_OFFICE, SALES, QUOTA FROM SALESREPS NAME REP_OFFICE SALES QUOTA -------------- ----------- ------------ -----------Bill Adams 13 $367,911.00 $350,000.00 Mary Jones 11 $392,725.00 $300,000.00 Sue Smith 21 $474,050.00 $350,000.00 Sam Clark 11 $299,912.00 $275,000.00 Bob Smith 12 $142,594.00 $200,000.00 Dan Roberts 12 $305,673.00 $300,000.00 Tom Snyder NULL $75,985.00 NULL Larry Fitch 21 $361,865.00 $350,000.00 Paul Cruz 12 $286,775.00 $275,000.00 Nancy Angelli 22 $186,042.00 $300,000.00
SQL also lets you ask for calculated results. For example, you can ask SQL to calculate the amount by which each salesperson is over or under quota:
SELECT NAME, SALES, QUOTA, (SALES - QUOTA) FROM SALESREPS NAME SALES QUOTA (SALES-QUOTA) -------------- ------------ ------------ -------------Bill Adams $367,911.00 $350,000.00 $17,911.00 Mary Jones $392,725.00 $300,000.00 $92,725.00 Sue Smith $474,050.00 $350,000.00 $124,050.00 Sam Clark $299,912.00 $275,000.00 $24,912.00 Bob Smith $142,594.00 $200,000.00 -$57,406.00 Dan Roberts $305,673.00 $300,000.00 $5,673.00 Tom Snyder $75,985.00 NULL NULL Larry Fitch $361,865.00 $350,000.00 $11,865.00 Paul Cruz $286,775.00 $275,000.00 $11,775.00 Nancy Angelli $186,042.00 $300,000.00 -$113,958.00
The requested data (including the calculated difference between sales and quota for each salesperson) once again appears in a row/column table. Perhaps you would like to focus on the salespeople whose sales are less than their quotas. SQL lets you retrieve that kind of selective information very easily, by adding a mathematical comparison to the previous request:
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