datamatrix c# library Figure 12-4. Pivot data results in C#.NET

Generator Data Matrix in C#.NET Figure 12-4. Pivot data results

Figure 12-4. Pivot data results
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UNPIVOT
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The reverse of PIVOT is, of course, UNPIVOT, which will unpivot data by placing column data into rows. You can prove this by unpivoting the data just pivoted using the preceding query. The code that follows will rebuild the pivot and place the data into a temporary table. From that temporary table, you can unpivot the data.
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Note UNPIVOT is not the exact reverse of PIVOT. PIVOT performs an aggregation and hence merges possible multiple rows into a single row in the output. UNPIVOT does not reproduce the original table-valued expression result because rows have been merged. Besides, NULL values in the input of UNPIVOT disappear in the output, whereas there may have been original NULL values in the input before the PIVOT operation.
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USE AdventureWorks go SELECT pt.Discount,ISNULL([711],0.00) As Product711, ISNULL([747],0.00) As Product747,ISNULL([776],0.00) As Product776 INTO #Temp1 FROM (SELECT sod.LineTotal, sod.ProductID, sod.UnitPriceDiscount as Discount FROM Sales.SalesOrderDetail sod) so
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CHAPTER 12 ADVANCED T-SQL
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PIVOT ( SUM(so.LineTotal) FOR so.ProductID IN ([776], [711], [747]) ) AS pt ORDER BY pt.Discount UNPIVOT has similarities to PIVOT in that you build a CTE in this case calling it upl which you then use as the basis of unpivoting. Once the CTE is defined, you then use UNPIVOT with the column definitions of the columns to create, DiscountAppl and ProductID where using IN defines the rows that will be produced back from the UNPIVOT. SELECT ProductID,Discount, DiscountAppl FROM (SELECT Discount, product711, Product747, Product776 FROM #Temp1) up1 UNPIVOT ( DiscountAppl FOR ProductID IN (Product711, Product747, Product776)) As upv2 WHERE DiscountAppl <> 0 ORDER BY ProductID When the preceding code is executed, the data is unpivoted, as shown in Figure 12-5.
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Figure 12-5. Unpivotted data results Now that we have pivoted data, we can take a look at how we can rank output.
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Ranking Functions
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With SQL Server 2005, it s now possible to rank rows of data in your T-SQL code. Ranking functions give you the ability to rank each row of data to provide a method of organizing the output in an ascending sequence. You can give each row a unique number or each group of similar rows the same number. You may be wondering what is wrong with other methods of ranking data, which might include IDENTITY columns. These types of columns do provide unique numbers, but gaps can form. You are also tied in to each row having its own number when you may wish to group rows together. So then, why not GROUP BY Well, yes, you can use GROUP BY, but what if the grouping was over more than one column In this case, processing the data further would require knowledge about those columns. Ranking functions make it possible to provide a value that allows data
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CHAPTER 12 ADVANCED T-SQL
to be ranked in the order required, and then that value can be used for splitting the data into further groupings. There are four ranking functions, which will be discussed in detail in upcoming sections: ROW_NUMBER: Allows you to provide sequential integer values to the result rows of a query. RANK: Provides an ascending, nonunique ranking number to a set of rows, giving the same number to a row of the same value as another. Numbers are skipped for the number of rows that have the same value. DENSE_RANK: Similar to RANK, but each row number returned will be one greater than the previous setting, no matter how many rows are the same. NTILE: Takes the rows from the query and places them into an equal (or as close to equal as possible) number of specified numbered groups, where NTILE returns the group number the row belongs to.
Note These ranking functions can only be used with the SELECT and ORDER BY statements. (Sadly, they
can t be used directly in a WHERE or GROUP BY clause, but you can use them in a CTE or derived table.
WITH OrderedOrders AS (SELECT SalesOrderID, OrderDate, ROW_NUMBER() OVER (order by OrderDate)as RowNumber FROM Sales.SalesOrderHeader ) SELECT * FROM OrderedOrders WHERE RowNumber between 50 and 60; The syntax for ranking functions is shown as follows: <function_name>() OVER([PARTITION BY <partition_by_list>] ORDER BY <order_by_list>) Taking each option as it comes, you can see how this can be placed within a SELECT statement, for example: function_name: Can be one of ROW_NUMBER, RANK, DENSE_RANK, and NTILE OVER: Defines the details of how the ranking should order or split the data PARTITION BY: Details which data the column should use as the basis of the splits ORDER BY: Details of the ordering of the data
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