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This chapter is on Web Services in the .NET Framework. We ll take a look at why you would want to use Web Services, we ll examine them from a vendor-neutral perspective to see how they provide for excellent cross-platform interoperability, and then we ll delve into some of the new features for Web Services that are built into version 2.0 of the .NET Framework. We ll wrap this chapter up with a quick look at Web Service Enhancements, an add-on package of functionality available from Microsoft.

A common table expression (CTE) is a bit like a temporary table It s transient, lasting only as long as the query requires it Temporary tables are available for use during the lifetime of the session of the query running the code or until they are explicitly dropped The creation and use of temporary tables is a two- or three-part phase: table creation, population, and use A CTE is built in the same code line as the SELECT, INSERT, UPDATE, or DELETE statements that use it The best way to understand a CTE is to demonstrate an example with some code Within the AdventureWorks database, there are a number of products held in the ProductionProduct table For this example, let s say you want to know the maximum list price of stock you re holding over all the product categories.

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A StackPanel is another layout element, and its claim to fame is that it will position content inside of it for you in a stacking manner (horizontally or vertically). This is different from the Grid or Canvas, which rely on

Now, suppose this process runs at night on a machine with four CPUs, and it is the only activity taking place. You have observed that only one CPU is partially used on this system, and the disk system is not being used very much at all. Further, this process is taking hours, and every day it takes a little longer as more data is added. You need to reduce the runtime dramatically it needs to run four or eight times faster so incremental percentage increases will not be sufficient. What can you do There are two approaches you can take. One approach is to implement a parallel pipelined function, whereby Oracle will decide on appropriate degrees of parallelism (assuming you have opted for that, which would be recommended). Oracle will create the sessions, coordinate them, and run them, very much like the previous example with parallel DDL where, by using CREATE TABLE AS SELECT or INSERT /*+APPEND*/, Oracle fully automated parallel direct path loads for us. The other approach is DIY parallelism. We ll take a look at both approaches in the sections that follow.

Using a temporary table, this would be a two-part process, as follows: USE AdventureWorks GO SELECT pProductSubcategoryID, sName,SUM(ListPrice) AS ListPrice INTO #Temp1 FROM ProductionProduct p JOIN ProductionProductSubcategory s ON sProductSubcategoryID = pProductSubcategoryID WHERE pProductSubcategoryID IS NOT NULL GROUP BY pProductSubcategoryID, sName.

class MyClass { bool UseSingleDeck = false, UseBigPics = false, UseFancyNums = false, UseAnimation = false; public void SetOptions2(CardDeckSettings ops) { UseSingleDeck = (ops & CardDeckSettings.SingleDeck) == CardDeckSettings.SingleDeck; UseBigPics = (ops & CardDeckSettings.LargePictures) == CardDeckSettings.LargePictures; UseFancyNums = (ops & CardDeckSettings.FancyNumbers) == CardDeckSettings.FancyNumbers; UseAnimation = (ops & CardDeckSettings.Animation) == CardDeckSettings.Animation; } public void PrintOptions() { Console.WriteLine("Option settings:"); Console.WriteLine(" Use Single Deck Console.WriteLine(" Use Large Pictures Console.WriteLine(" Use Fancy Numbers Console.WriteLine(" Show Animation } } class Program { static void Main() { MyClass mc = new MyClass(); CardDeckSettings ops = CardDeckSettings.SingleDeck | CardDeckSettings.FancyNumbers | CardDeckSettings.Animation; mc.SetOptions2(ops); mc.PrintOptions(); } }

Another important measure of SQL performance is the resource utilization per execution (DB time/execute, CPU/execute). The values in testing will be compared to those in production to verify that no significant changes are evident. This data should be saved for future reference, along with the statement s execution plans. If possible, save important queries stored outlines; these are often a fast track for developers, which can be used during problem debugging. This way, should anything not perform as expected in production, some diagnostic data is already available so you can work out what has changed and why the performance has degraded.

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