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Besides the existing fields of a dataset, you can create new ones using several methods. You can create calculated fields based on existing fields, or you can use aggregate functions such as Sum, Avg, and Count.
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Carsten Ziegeler is a member of the Apache Software Foundation and as such is involved in various open source communities, like Cocoon, Avalon, and Excalibur. He is a member of the Apache Portals project management committee and committer of the Pluto and the WSRP4J project. In paid life, Carsten is the chief architect of the Open Source Group at S&N AG, Paderborn, Germany. The focus is on Java-based middleware functionality such as web frameworks, component architectures, and portal solutions and technologies. The liaison to Apache started in 2000 when Carsten became committer of the Cocoon project and started to play an important role in designing and developing the current architecture. A major contribution to Cocoon is the standard-compliant Cocoon Portal.
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an order to be shipped only once payment has been approved and stock level has been verified. Payment approval comes from a financial system, and stock-level information comes from an inventory system. Once both systems publish their respective messages for a specific order, that order can be delivered to the customer. Parallel convoys are implemented by message correlation and Parallel Action shapes in BizTalk Server, as shown in the following steps. 1. Open the project that contains the schemas. (We assume that XSD schemas used to define payment approval and stock-level verification messages are already created.) Add a new orchestration to the project, and give it a descriptive name. In our example, the orchestration is named ParallelConvoyOrchestration. Create two new messages, and specify the name and type of each. In our example, we create messages named PaymentApprovalMessage and StockLevelConfirmationMessage, which are defined by the PaymentApprovalSchema and StockLevelConfirmationSchema schemas, respectively. In the Orchestration View window, expand the Types node of the tree view so that the Correlation Types folder is visible. Right-click the Correlation Types folder, and select New Correlation Type, which creates a correlation type and launches the Correlation Properties dialog box. In the Correlation Properties dialog box, select the properties that the correlation will be based on. In our scenario, we select the OrderID property, which has been promoted from the PaymentApprovalSchema and StockLevelConfirmationSchema schemas. Click the new correlation type, and give it a descriptive name in the Properties window. In our example, the correlation type is named OrderIDCorrelationType. In the Orchestration View window, right-click the Correlation Set folder, select New Correlation Set, and specify a name and correlation type. In our example, we create a correlation set named OrderIDCorrelationSet and select OrderIDCorrelationType. From the toolbox, drag the following onto the design surface in top-down order; the parallel convoy configuration is shown in Figure 5 44: Parallel Actions shape to receive the response from the financial and inventory systems. Receive shape to receive messages from the financial system. Place this shape on the left-hand branch of the Parallel Actions shape. Configure this shape to use the PaymentApprovalMessage, to initialize the OrderIDCorrelationSet, to activate the orchestration, and to use an orchestration receive port. Receive shape to receive messages from the inventory system. Place this shape on the right-hand branch of the Parallel Actions shape. Configure this shape to use the StockLevelConfirmationMessage, to initialize the OrderIDCorrelationSet, to activate the orchestration, and to use an orchestration receive port.
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You can see that although this model is easy to use, there are drawbacks to other aspects. The most important aspect is that the source code in a clear text version must be placed on the deployment platform. Luckily, the .NET Framework 2.0 provides some additional options and techniques to use so the disadvantages are minimized. We will start off the discussion in the next section with precompilation.
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You can also use range and sequence expressions to build list and array values. The syntax is identical, except the surrounding braces are replaced by the usual [ ] for lists and [| |] for arrays ( 4 discusses arrays in more detail): > [ 1 .. 4 ];; val it: int list = [ 1; 2; 3; 4 ] > [ for i in 0 .. 3 -> (i,i*i) ];; val it : (int * int) list = [ (0,0); (1,1); (2,4); (3,9) ] > [| for i in 0 .. 3 -> (i,i*i) |];; val it : (int * int) [] = [ (0,0); (1,1); (2,4); (3,9) ]
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If the change is successful, then you will see the following output:
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