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The goal in this case will be to generate a result row for each customer and year, containing the customer ID (custid), order year (orderyear), and quantity (qty). I'll start with a solution that applies to versions earlier than SQL Server 2005. Here as well, try to think in terms of query logical processing as described in 1. The first and most important step in the solution is to generate three copies of each base rowone for each year. This can be achieved by performing a cross join between the base table and a virtual auxiliary table that has one row per year. The SELECT list can then return the custid and orderyear, and also calculate the target year's qty with the following CASE expression: CASE orderyear WHEN 2002 THEN [2002] WHEN 2003 THEN [2003] WHEN 2004 THEN [2004] END AS qty

This query generates (on my system) the following output:

When you re done, run the following code for cleanup:

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db ------------------Performance MDW AdventureWorks2008 Performance MDW tempdb Northwind msdb master msdb Generic model tempdb pubs InsideTSQL2008 Generic master AdventureWorks2008 Northwind InsideTSQL2008 pubs model type_desc ---------ROWS ROWS ROWS LOG LOG ROWS ROWS LOG ROWS ROWS LOG ROWS LOG ROWS ROWS ROWS LOG LOG LOG LOG LOG LOG io_mb --------26002.09 1495.23 99.82 121.43 625.91 107.40 38.39 64.63 58.13 149.90 1.05 8.52 7.34 4.57 4.50 4.32 1.07 0.23 0.07 0.12 0.41 0.56 io_stall_s ----------14364.84 834.43 311.11 275.64 177.80 147.05 117.32 104.98 100.44 89.24 12.25 3.66 3.54 2.64 2.35 1.74 1.61 1.59 1.30 1.09 0.96 0.40 io_stall_pct ------------86.77 5.04 1.88 1.66 1.07 0.89 0.71 0.63 0.61 0.54 0.07 0.02 0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.00 rn --1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

IF OBJECT_ID('dbo.T1', 'U') IS NOT NULL DROP TABLE dbo.T1;

You achieve unpivoting this way, but you'll also get rows corresponding to NULL values in the source table (for example, for customer D in years 2003 and 2004). To eliminate those rows, create a derived table out of the solution query and, in the outer query, eliminate the rows with the NULL in the qty column.

The output shows the database name, le type, total I/O (reads and writes) in megabytes, I/O stalls in seconds, I/O stalls in percent of the total for the whole system, and a row number indicating a position in the sorted list based on I/O stalls. Of course, if you want, you can calculate a percentage and row number based on I/O as opposed to I/O stalls, and you can also use running aggregation techniques to calculate a running percentage, as I demonstrated earlier. You might also be interested in a separation between the reads and writes for your analysis. In this output, you can clearly identify the main element involving most of the system s I/O stalls the data portion of Performance, which scores big time (86 percent of the stalls), and the data portion of MDW, which also incurs a large percent (5 percent of the stalls). I enabled the data collector in my system and the three system collection sets, which store the information in this management data warehouse. By default, the collection frequency is 60 seconds. Behind, with about 1 to 2 percent each, are the data portions of AdventureWorks2008 and tempdb and the log portions of Performance and MDW. Obviously, you should focus on these elements, paying special attention to data activity against the Performance database.

1

The following example demonstrates how to use an INSTEAD OF TRIGGER to support UPDATE statements against a view that would have not been supported otherwise . Suppose that you have a table with order details and a view that aggregates order detail quantities per order . Run the following code to create the OrderDetails table, populate it with sample data, and create the OrderTotals view, which calculates the sum of the quantity for each order:

the WHERE phase. In fact, expression aliases cannot even be used by other expressions within the same SELECT list. The reasoning behind this limitation is another unique aspect of SQL; many operations are all-at-once operations. For example, in the following SELECT list, the logical order in which the expressions are evaluated should not matter and is not guaranteed: SELECT c1 + 1 AS e1, c2 + 1 AS e2. Therefore, the following SELECT list is not supported: SELECT c1 + 1 AS e1, e1 + 1 AS e2. You re allowed to use column aliases only in steps following the SELECT phase, such as the ORDER BY phase for example, SELECT YEAR(orderdate) AS orderyear . . . ORDER BY orderyear. The concept of an all-at-once operation can be hard to grasp. For example, in most programming environments, to swap values between variables you use a temporary variable. However, to swap table column values in SQL, you can use:

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