Designing and Executing Map
Transformations are created using the Map Editor in Studio IDE. It includes a graphical user interface (GUI) for designing transformations and data transformation read or write modules.
The Map Editor GUI includes all the tools that you need to specify an end-to-end transformation. These design rules are saved in a transformation specification file under a unique name. These specification files can be executed interactively in the Map Editor environment (suitable for ad-hoc testing and prototyping) or through a custom application.
The read or write modules use specialized data transformation components called connectors. Connectors are the foundation for the transformation architecture upon which Map Editor is built. Data transformation is facilitated by importing data from a source data format and then exporting the data in another format to the target. The connectors handle the data import and export operations.
Each connector is designed to convert data to or from one specific data format. Connectors that read are referred to as import connectors. Connectors that write are referred to as export connectors. The ability to plug and play different connectors to convey data means that the connectors are both flexible and highly efficient. Data can easily be converted in real time on limited record sets, or in bulk quantities for large loads and migrations.
Topics:
Using the map editor, you can design and run maps that include data transformation instructions for an integration project.
At the basic level, a map consists of the following:
• Map metadata properties (metadata properties such as creator, create date, date modified, and description)
• Maps use datasets to read and write data. The source datasets are read, and the target datasets are written. You select source or target when you create a dataset.
Tip: You can design a map using source and target datasets and switch to other datasets in the configuration that runs the map.
• Source contains the following:
– Connect information (parts and properties)
– Schema (defines record, field, and field datatype information that enables the connector to parse the data and pass it in a common format to the engine). Some connectors have built-in schemas. For other connectors, you must set an external schema that can be used by the connector.
– Sort keys (can be set if source schema has one record type)
– Filters (allows you to fine tune the data you want to transform)
– Sample settings
• Targets:
– Connect information (parts and properties)
– Schema (defines record, field, and field datatype information that enables the connector to parse the data and pass it in a common format to the engine). Some connectors have built-in schemas. For other connectors, you must set an external schema that can be used by the connector.
– Update keys (only for connectors that supports Update as the output mode)
– Filters (allows you to fine tune the data you want to transform, not applicable for reject)
• Map that includes:
– Field mapping (from source to target)
– Events and actions (at the transformation, source, target, or source/target record level)
– Recognition rules (only for XML-based map)
– Validation rules (only for XML-based map)
– Put rules (target only, XML-based map)
• Configuration settings
– Macros
– Script Libraries (contain functions that can be executed while transforming data)
– Global Variables (used in expressions)
– Map events (for pre and post data transformation processing)
– Execution Configuration
• Execution properties
• Log settings
• Profile settings
The actual mapping has two views Map Fields (Simple) View and a Map All (Advanced) View. The Advanced view allows to set events and actions. In case of XML-based map, you can also specify the recognition rules, validation rules, and put rules.
For more information about the types of artifacts and the supported editors, see
DataConnect Integration Artifacts and Editors.