Dynamic Workflows: Basics of Dynamics

Liz Sanderson
Liz Sanderson
  • Updated

FME Version

  • FME 2022.0

Why Create Dynamic Workspaces?

Traditional FME Workspaces are tightly bound to the source and destination schemas:

ParksMapping.png

A dynamic workspace breaks this dependence on schema creating a universal layout that is designed to handle data regardless of the schema:

Components of a Dynamic Workflow

A number of components can be made dynamic in an FME Workspace:

Source Feature Types
In the Reader, a source Feature Type can be configured to read any schema. This can be set using the Merge Filter parameter.

MergeFT.png

Destination Feature Types
In the Writer, a destination Feature Type can be configured to write the schema defined at runtime.

SchemaFromTable.png

Note: There is a related function not discussed in this series: the feature type fanout. A fanout will split output data based upon the value of an attribute at runtime. Read more about fanouts.
 

Common Uses for Dynamic Workflows

Dynamic workflows can be useful for cases like:

  • Applying a relatively simple data transformation to all data coming into a workflow, regardless of its schema (for example, clipping, format translations, coordinate transformations).
  • When the source dataset's schema is not predictable or well defined.
  • Performing ad hoc data transformations on many input datasets.
  • When the destination format might vary.
  • When long-term maintenance of the workspace is required (for example, if new feature types or attributes are added to the source data, the workspace would not need to be changed).

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