Dynamic workspaces are a way of providing maximum translation flexibility and minimizing the longer-term maintenance of workspaces.
Dynamic means that the workspace will be set up very simply, but with maximum flexibility. You can read any source dataset (of the chosen format) and it will be read and written (to the destination format) correctly. The important part is that you can change the source to a different dataset, and it will still work.
Traditional FME Workspaces are very tightly bound to the source and destination schemas. In many cases, this is what you will want. However, in certain situations, the workspace needs to be more independent of the schemas.
A dynamic workspace breaks the dependence on the source and destination schema. Common applications for dynamic workspaces are:
While translations are generally very easy to implement using FME Workbench, in the longer term they can require a lot of maintenance to keep up-to-date. If new feature types or attributes are added to the source data, you must also update the workspace. Sometimes you may not even realize that a data owner has changed their data schema.
There are a number of components that you could make dynamic in an FME workspace:
Schema: Source Feature Types
A workspace that would read any set of feature types from a source dataset
This is supported by the Merge Filter
Schema: Destination Feature Types
A workspace that would read any set of feature types from a source dataset , and would write a corresponding set of feature types
This is supported by the Dynamic mode
Schema: Attributes
A workspace that would read any set of attributes on the source feature types and write them out in the same schema
This is supported by Dynamic mode
Format
A workspace that would write to any format, without the need to add multiple writers
This is supported by the Generic Writer