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map needs to perform until runtime, or static links may not be practical because of a large number of possible groups. When inline XSLT performs the grouping, BizTalk applies the filter expression to the //Sale statement, which means BizTalk applies the filter expression to every Sale element in the input message. For each input message, the expression checks the value of every preceding-sibling and returns true when none of the preceding-sibling elements has the same RepName value. This algorithm is not efficient for large messages. There is a generally more efficient alternative XSLT approach to the group by problem. This alternative approach is the Muenchian method. The Muenchian method is generally more efficient than the inline solution presented here, but the default BizTalk functoids cannot implement it. The Muenchian method declares an xsl:key element at the top level of the XSLT style sheet. The map directly obtains a node set for each distinct RepName with an xsl:key, eliminating the computational cost of checking every preceding sibling incurred with inline XSLT. However, since the top level of the xsl:stylesheet element must declare the xsl:key element, inline XSLT cannot implement it. Only a separate style sheet file can implement the Muenchian method. Place the XSLT style sheet in Listing 3 43 in a separate file for this example. Listing 3 43. Sample Group-By Style Sheet < xml version="1.0" > <xsl:stylesheet xmlns:xsl="http://www.w3.org/1999/XSL/Transform" version="1.0"> <xsl:key name="SalesByRepKey" match="Sale" use="RepName"/> <xsl:template match="/"> <ns0:SalesByRep xmlns:ns0='http://tempURI.org'> <xsl:apply-templates select="//Sale[generate-id()= generate-id(key('SalesByRepKey', RepName)[1])]"/> </ns0:SalesByRep> </xsl:template> <xsl:template match="Sale"> <RepSales> <RepTotalAmount> <xsl:value-of select="sum(key('SalesByRepKey', RepName)/Amount)" /> </RepTotalAmount> <RepName> <xsl:value-of select="RepName" /> </RepName> </RepSales> </xsl:template> </xsl:stylesheet> Specify the external XSLT file used by a BizTalk map (see the next recipe for steps on doing this).

Sometimes data that users need to fill the report with is found in plain text files, in a certain format, such as the popular CSV (comma-separated value). JasperReports provides an implementation for such a data source, by wrapping the CSV data from a text file into a net.sf.jasperreports.engine.data.JRCsvDataSource.

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hip holster. The setting was on Loud and all in the room heard it: Oooooooh! Ahhhh! Ohhh! Oh Yes! YES! YES! I fumbled for the phone to turn it off and explained to the class, This is a demonstration of what not to do in my class! Doreen, Psychology Professor So far we have made a moral inventory of our BlackBerry use and abuse. All of us probably find ourselves lacking in some way. Maybe we are even saddened and embarrassed by the reality of our rude and selfish behavior. Keep reading. In the rest of this chapter, we ll cover strategies that will help you restore order to your life and curb your bad BlackBerry behavior.

You are fed up with the mapper and can t stand using functoids. You have a complex map that you feel like getting done programmatically, and you want to shell out to real XSLT.

It is quite simple to shell out to an XSLT document. Take these steps: 1. 2. 3. Right-click the map surface, and select Properties. Click the ellipsis next to the Custom XSLT Path property, and open the file containing the custom XSLT. Compile the map. The XSLT file is included in the BizTalk assembly and does not need to be deployed separately.

Sometimes, it is best to use XSLT directly, instead of using the BizTalk mapping functionality. This can be for a variety of reasons but generally is useful when there is a lot of complex mapping that uses IfThen-Else to populate fields. Because this type of logic can get complex with the use of Value Mapping functoids, pure XSLT can be much easier to use. See Figure 3 62.

The CSV data source usually needs to read a file from disk, or at least from an input stream Thus, the JRCsvDataSource can be initialized in three ways, depending on where it gets the data: A file: new JRCsvDataSource(File) An input stream: new JRCsvDataSource(InputStream) A reader: new JRCsvDataSource(Reader) The CSV format has certain formatting rules Data rows are separated by a record delimiter (text sequence) and fields inside each row are separated by a field delimiter (character) Fields containing delimiter characters can be placed inside quotes If fields contain quotes themselves, these are duplicated (eg, "John ""Doe""" will be displayed as John "Doe") The default values in JasperReports (and also the most common for CSV files) are a comma for field delimiter and a newline (\n) for record delimiter Users can override these default values by calling setFieldDelimiter(char) and setRecordDelimiter(String).

For the purposes of testing, there are two basic types of maps: Simple maps, which consist of a single source schema and single destination schema Complex maps, which consist of two or more source schemas and/or two or more destination schemas

This solution will work through both types, illustrating several techniques for creating the necessary input documents and obtaining the test results. Figure 3 63 shows a simple map, with a Company schema being mapped from a combination of a Person schema and hard-coded values in two String Concatenate functoids.

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