free barcode generator using vb.net Figure 7-2: Manually processing a multi-table query in Software

Print Quick Response Code in Software Figure 7-2: Manually processing a multi-table query

Figure 7-2: Manually processing a multi-table query
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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
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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. Of course this isn't the only way to generate the query results, but regardless of how you do it, two things will be true: Each row of query results draws its data from a specific pair of rows, one from the ORDERS table and one from the CUSTOMERS table. The pair of rows are found by matching the contents of corresponding columns from the tables.
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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 multi-table 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 multi-table queries by matching columns, it should come as no surprise that the SELECT statement for a multi-table query must contain a search 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. SELECT ORDER_NUM, AMOUNT, COMPANY, CREDIT_LIMIT FROM ORDERS, CUSTOMERS WHERE CUST = CUST_NUM ORDER_NUM ---------112989 112968 112963 112987 112983 113027 112993 113065 113036 113034 AMOUNT COMPANY -------------------------$1,458.00 Jones Mfg. $3,978.00 First Corp. $3,276.00 Acme Mfg. $27,500.00 Acme Mfg. $702.00 Acme Mfg. $4,104.00 Acme Mfg. $1,896.00 Fred Lewis Corp. $2,130.00 Fred Lewis Corp. $22,500.00 Ace International $632.00 Ace International CREDIT_LIMIT -----------$65,000.00 $65,000.00 $50,000.00 $50,000.00 $50,000.00 $50,000.00 $65,000.00 $65,000.00 $35,000.00 $35,000.00
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This looks just like the queries from the previous chapter, with two new features. First, the FROM clause lists two tables instead of just one. Second, the search condition: CUST = CUST_NUM compares columns from two different tables. We call these two columns the matching columns for the two tables. Like all search conditions, this one restricts the rows that appear in the query results. Because this is a two-table query, the search condition restricts the pairs of rows that generate the query results. In fact, the search condition specifies the same matching columns you used in the paper-and-pencil query processing. It actually captures the spirit of the manual column matching very well, saying: "Generate query results only for pairs of rows where the customer number (CUST) in the ORDERS table matches the customer number (CUST_NUM) in the CUSTOMERS table." Notice that the SELECT statement doesn't say anything about how SQL should execute the query. There is no mention of "starting with orders" or "starting with customers." Instead, the query tells SQL what the query results should look like and leaves it up to SQL to decide how to generate them.
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