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CHAPTER 6 QUERYING MULTIPLE DATABASE OBJECTS AND MANIPULATING RESULT SETS
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In highly normalized databases, such as the AdventureWorks database, you will frequently have the opportunity to merge rows from four, or even more, tables when trying to compose a result set. Recall that when you merge rows from multiple tables, you need to consider how you are going to handle null values. Using a left join forces all rows from one table into the result set even if its rows have null values for merge columns. If you do not use a left or right join, then rows with null values may be excluded from a result set for a typical join between two data sources when merge column values equal each other. This section illustrates the syntax for both approaches. The next SELECT statement shows a four-table join between the SalesPerson, Employee, Contact, and SalesTerritory tables. Adding the SalesTerritory table allows the use of Name column values from the SalesTerritory table instead of the more cryptic TerritoryID column values from the SalesPerson table. The fourth table, SalesTerritory, is appended to the end of the FROM clause from the preceding SELECT statement with a LEFT JOIN clause. The LEFT JOIN clause allows you to retain rows with null TerritoryID column values in the result set. SELECT t.Name 'Territory name', s.SalesPersonID, s.SalesQuota, c.LastName FROM Sales.SalesPerson s JOIN HumanResources.Employee e ON s.SalesPersonID = e.EmployeeID JOIN Person.Contact c ON e.ContactID = c.ContactID LEFT JOIN Sales.SalesTerritory t ON s.TerritoryID = t.TerritoryID ORDER BY s.TerritoryID The next result set listing shows all 17 rows returned by the preceding SELECT statement. These rows correspond to the 17 rows in the SalesPerson table with added columns from the Contact and SalesTerritory tables. The Territory name column values in the result set are from SalesTerritory table. The LastName column values are from the Contact table. The first three rows in the result set have null Territory name column values because these rows have null values for TerritoryID in the SalesPerson table. Without the use of a LEFT JOIN to add the TerritoryID column of values to the join of the SalesPerson, Employee, and Contact tables, the rows with null TerritoryID values would fail to be incorporated in the result set. The result set rows are ordered by TerritoryID values. Because TerritoryID column values map to territory names but don t reflect alphabetical order, the rows are grouped by Territory name but aren t in ascending alphabetical order. Territory name -------------NULL NULL NULL Northwest Northwest Northwest Northeast Central Southwest Southwest Southeast Canada Canada France SalesPersonID ------------268 284 288 287 280 283 275 277 276 281 279 282 278 286 SalesQuota ---------NULL NULL NULL 300000.00 250000.00 250000.00 300000.00 250000.00 250000.00 250000.00 300000.00 250000.00 250000.00 250000.00 LastName ----------------Jiang Alberts Abbas Mensa-Annan Ansman-Wolfe Campbell Blythe Carson Mitchell Ito Reiter Saraiva Vargas Varkey Chudukatil
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CHAPTER 6 QUERYING MULTIPLE DATABASE OBJECTS AND MANIPULATING RESULT SETS
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Instead of just listing values, you will sometimes need to aggregate column values by group or even compute calculated columns for a result set. The next four-table join illustrates how to perform these tasks with a four-table join as a data source. The SELECT statement integrates design techniques from previous samples in this section. The SELECT list designates four columns: The first column is the Name column from the SalesTerritory table. The second and third columns are two aggregated columns that compute the sum of the SalesYTD and SalesLastYear column values from the underlying SalesPerson table. The fourth column is a calculated column that uses the difference between the sum of SalesYTD and the sum of SalesLastYear column values to compute the percent change in sales between the two years. The FROM clause specifies the four tables that compose the data source. These input tables to the merged data source enable the computing of aggregates by territory name. An inner join merges the SalesTerritory table with the join for the preceding three tables. By using an inner join, rows with null TerritoryID column values from the SalesPerson table are dropped from the computation of aggregates. This is reasonable because you do not know to which territory you should assign the sales for the three sales persons without TerritoryID assignments. The GROUP BY clause groups rows in the data source with the same Name column value from the SalesTerritory table. The ORDER BY clause orders the result set rows in ascending alphabetical order. SELECT t.Name 'Territory name', SUM(s.SalesYTD) 'YTD Sales', SUM(s.SalesLastYear) 'Sales last year', CAST(((SUM(s.SalesYTD) - SUM(s.SalesLastYear))/ SUM(s.SalesLastYear))*100 AS DEC(12,2)) 'Percent change' FROM Sales.SalesPerson s JOIN HumanResources.Employee e ON s.SalesPersonID = e.EmployeeID JOIN Person.Contact c ON e.ContactID = c.ContactID JOIN Sales.SalesTerritory t ON s.TerritoryID = t.TerritoryID GROUP BY t.Name ORDER BY t.Name The result set listing for the preceding SELECT statement appears next. The listing contains just 10 rows one for each of the sales territories. You may wish to revise the SELECT list so that YTD Sales and Sales last year columns appear with just two places after the decimal point. If you decided to make that adjustment, you should make a corresponding change in the calculated Percent change column. Otherwise, some consumers of the report may complain about the computational accuracy of your reports. Territory name -------------Australia Canada YTD Sales -----------1758385.926 4954295.2324 Sales last year --------------2278548.9776 3658511.5515 Percent change --------------22.82 35.41
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