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There is a link between these two tables, however. In each row of the ORDERS table, the CUST column contains the customer number of the customer who placed the order, which matches the value in the CUST_NUM column in one of the rows in the CUSTOMERS table. Clearly, the SELECT statement that handles the request must somehow use this link between the tables to generate its query results. Before examining the SELECT statement for the query, it s instructive to think about how you would manually handle the request, using paper and pencil. Figure 7-2 shows what you would probably do: 1. Start by writing down the four column names for the query results. Then move to the ORDERS table, and start with the first order. 2. Look across the row to find the order number (112961) and the order amount ($31,500.00), and copy both values to the first row of query results. 3. Look across the row to find the number of the customer who placed the order (2117), and move to the CUSTOMERS table to find customer number 2117 by searching the CUST_NUM column. 4. Move across the row of the CUSTOMERS table to find the customer s name ( J.P. Sinclair ) and credit limit ($35,000.00), and copy them to the query results table. 5. You ve generated a row of query results! Move back to the ORDERS table, and go to the next row. Repeat the process, starting with Step 2, until you run out of orders.

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year. With the market power of Microsoft behind it, and the open standards blessing of the SQL Access Group, ODBC has emerged as the de facto standard interface for PC access to SQL databases. Apple and Microsoft announced an agreement to support ODBC on Macintosh and Windows in the spring of 1993, giving ODBC industry standard status in both popular graphical user interface environments. ODBC implementations for UNIX-based systems soon followed. In 1995, the ODBC interface effectively became an ANSI/ISO standard, with the publication of the SQL/Call-Level Interface (CLI) standard. Today, ODBC is in its fourth major revision as a cross-platform database access standard. ODBC support is available for all major DBMS brands. Most packaged application programs that have database access as an important part of their capabilities support ODBC, and they range from multimillion-dollar enterprise-class applications like Enterprise Resource Planning (ERP) and Supply Chain Management (SCM) to PC applications such as spreadsheets, query tools, and reporting programs. Microsoft s focus has moved beyond ODBC to higher-level interfaces (such as OLE/DB) and more recently to Active/X Data Objects (ADO), but these new interfaces are layered on top of ODBC for relational database access, and it remains a key cross-platform database access technology.

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Figure 7-1.

The SUM() column function computes the sum of a column of data values. The data in the column must have a numeric type (integer, decimal, floating point, or money). The result of the SUM() function has the same basic data type as the data in the column, but the result may have a higher precision. For example, if you apply the SUM() function to a column of 16-bit integers, it may produce a 32-bit integer as its result. Here are some examples that use the SUM() column function: What are the total quotas and sales for all salespeople SELECT SUM(QUOTA), SUM(SALES) FROM SALESREPS SUM(QUOTA) SUM(SALES) -------------- ------------$2,700,000.00 $2,893,532.00 What is the total of the orders taken by Bill Adams SELECT SUM(AMOUNT) FROM ORDERS, SALESREPS WHERE NAME = 'Bill Adams' AND REP = EMPL_NUM SUM(AMOUNT) -----------$39,327.00

Multitable Queries (Joins)

Figure 7-2.

CUSTOMERS Table CUST_NUM COMPANY 2108 Holm & Landis 2117 J.P. Sinclair 2122 Three-Way Lines

Simple Joins (Equi-Joins)

109 106 105

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The process of forming pairs of rows by matching the contents of related columns is called joining the tables. The resulting table (containing data from both of the original tables) is called a join between the two tables. (A join based on an exact match between two columns is more precisely called an equi-join. Joins can also be based on other kinds of column comparisons, as described later in this chapter.) Joins are the foundation of multitable query processing in SQL. All of the data in a relational database is stored in its columns as explicit data values, so all possible relationships between tables can be formed by matching the contents of related columns. Joins thus provide a powerful facility for exercising the data relationships in a database. In fact, because relational databases do not contain pointers or other mechanisms for relating rows to one another, joins are the only mechanism for exercising cross-table data relationships. Because SQL handles multitable queries by matching columns, it should come as no surprise that the SELECT statement for a multitable query must contain a search

$55,000.00 $35,000.00 $30,000.00

Computing a Column Average (AVG)

ORDERS Table ORDER_NUM ORDER_DATE 112961 113012 112989 2 17-DEC-89 11-JAN-90 03-JAN-90

Multitable Queries (Joins)

AMOUNT $31,500.00 $3,745.00 $1,458.00 4 4

condition that specifies the column match. Here is the SELECT statement for the query that was performed manually in Figure 7-2: List all orders showing order number, amount, customer name, and the customer s credit limit.

1 QUERY Results ORDER_NUM 112961 AMOUNT $31,500.00

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