Anypoint DataMapper User Guide and Reference
Anypoint™ DataMapper, or DataMapper for short, is a Mule transformer that delivers simple, yet powerful, visual design of complex data transformations for use in Mule flows, including:
- Extraction and loading of flat and structured data formats
- Filtering, extraction and transformation of input data using XPath and powerful scripting
- Augmenting data with input parameters and lookups from other data sources
- Live design-time previews of transformation results
- High-performance, scalable data mapping operations
Inputs and outputs can be “flat” (that is, row-structured) data like CSV files or Excel spreadsheet data, or structured data in the formats supported throughout Mule: XML, JSON, key/value Maps and trees of Plain Old Java Objects (POJOs).
In general, using the more basic Mule transformers to recreate the functionality of a single DataMapper may require a complex flow of format converters for input data, splitters, filters, For Each scopes, expressions, other transformers, aggregators, and yet more format converters for the output. A DataMapper-based implementation is faster to implement and e asier to maintain than the alternatives.
Graphical design of the complex transformations supported by DataMapper makes it simple to apply all of its capabilities with little coding beyond basic expressions and function calls to transform data.
Using this Guide
The documentation for Anypoint Datamapper contains the following sections:
- DataMapper Concepts
- DataMapper Visual Reference
- Defining DataMapper Input and Output Metadata
- Building a Mapping Flow in the Graphical Mapping Editor
- Updating Metadata in an Existing Mapping
- Mapping Elements Inside Lists
- Previewing DataMapper Results on Sample Data
- DataMapper Examples
- DataMapper Supplemental Topics