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For example, if the name of the root element in the previous example's employee file is changed from "employee File" to "employees", and "title" was renamed "position", the mapping file could be updated as shown below.attribute on any mapping component (stream, group, record, segment or field).Before diving into the details, let's start with a basic example using the employee input file from Section 2.1 after it's been converted to XML (shown below).so that the XML document can be properly completed.Bean IO is ideally suited for batch processing, and currently supports XML, CSV, delimited and fixed length file formats. Bean IO 2.0 includes an entirely new parsing engine that supports the following enhancements: value for a group, record or field can be overridden using property values. To get started with Bean IO, download the latest stable version from Google Code, extract the contents of the ZIP file, and add to your application's classpath. In order to process XML formatted streams, Bean IO also requires an XML parser based on the Streaming API for XML (St AX), as specified by JSR 173.JDK 1.6 and higher includes a St AX implementation and therefore does not require any additional libraries.Because Bean IO is built like a pull parser, it does not support XML validation against a DTD or XML schema.

The following example illustrates some of the ways a template can be used: configurations bound to the bean.

JDK 1.5 users will need to include the following: Next, let's suppose we want to read records into the following Java bean for further processing.

Remember that a Java bean must have a default no-argument constructor and public getters and setters for all exposed properties.

When field trimming is enabled, , all validations are performed after the field's text has first been trimmed.

Field validations are ignored when writing to an output stream.

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Thrown when the underlying input stream is malformed based on the configured stream format, and therefore a record could not be accurately read from the stream.