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Calculate the total orders for each customer of each salesperson, sorted by customer, and within each customer by salesperson.
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SELECT FROM GROUP ORDER CUST, REP, SUM(AMOUNT) ORDERS BY CUST, REP BY CUST, REP
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CUST REP SUM(AMOUNT) ----- ---- -----------2101 106 $1,458.00 2102 101 $3,978.00 2103 105 $35,582.00 2106 102 $4,026.00 2107 110 $23,132.00 2108 101 $150.00 2108 109 $7,105.00 2109 107 $31,350.00 2111 103 $2,700.00 2111 105 $3,745.00 . . .
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Note that it s also impossible to get both detailed and summary query results from a single query. To get detailed query results with subtotals or to get multilevel subtotals, you must write an application program using programmatic SQL and compute the subtotals within the program logic. The original developers of SQL Server addressed this limitation of standard SQL by adding an optional COMPUTE clause to the end of the SELECT statement. The COMPUTE clause calculates subtotals and sub-subtotals, as shown in this example: Calculate the total orders for each customer of each salesperson, sorted by salesperson, and within each salesperson by customer.
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SELECT REP, CUST, AMOUNT FROM ORDERS ORDER BY REP, CUST COMPUTE SUM(AMOUNT) BY REP, CUST COMPUTE SUM(AMOUNT), AVG(AMOUNT) BY REP
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SQL: The Complete Reference
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REP CUST AMOUNT ---- ----- -------------101 2102 $3,978.00 sum -------------$3,978.00 REP CUST AMOUNT ---- ----- -------------101 2108 $150.00 sum -------------$150.00 REP CUST AMOUNT ---- ----- -------------101 2113 $22,500.00 sum -------------$22,500.00 sum -------------$26,628.00 avg -------------$8,876.00 REP CUST AMOUNT ---- ----- -------------102 2106 $2,130.00 102 2106 $1,896.00 sum -------------$4,026.00 REP CUST AMOUNT ---- ----- -------------102 2114 $15,000.00 sum -------------$15,000.00
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Summary Queries
REP CUST AMOUNT ---- ----- -------------102 2120 $3,750.00 sum -------------$3,750.00 sum -------------$22,776.00 avg -------------$5,694.00 . . .
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The query produces one row of detailed query results for each row of the ORDERS table, sorted by CUST within REP. In addition, it computes the sum of the orders for each customer/salesperson pair (a low-level subtotal) and computes the sum of the orders and average order size for each salesperson (a high-level subtotal). The query results thus contain a mixture of detail rows and summary rows, which include both subtotals and sub-subtotals. The COMPUTE clause is very nonstandard, and in fact, it is unique to the TransactSQL dialect used by SQL Server. Furthermore, it violates the basic principles of relational queries because the results of the SELECT statement are not a table, but a strange combination of different types of rows. Nonetheless, as the example shows, it can be very useful.
Restrictions on Grouped Queries
Grouped queries are subject to some rather strict limitations. The grouping columns must be actual columns of the tables named in the FROM clause of the query. You cannot group the rows based on the value of a calculated expression. There are also restrictions on the items that can appear in the select list of a grouped query. All of the items in the select list must have a single value for each group of rows. Basically, this means that a select item in a grouped query can be: I A constant I A column function, which produces a single value summarizing the rows in the group I A grouping column, which by definition has the same value in every row of the group I An expression involving combinations of these
SQL: The Complete Reference
In practice, a grouped query will always include both a grouping column and a column function in its select list. If no column function appears, the query can be expressed more simply using SELECT DISTINCT, without GROUP BY. Conversely, if you don t include a grouping column in the query results, you won t be able to tell which row of query results came from which group! Another limitation of grouped queries is that SQL ignores information about primary keys and foreign keys when analyzing the validity of a grouped query. Consider this query: Calculate the total orders for each salesperson.
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