AreaOnAreaOverlayer

This transformer accepts area features as input. Area features are expected to be non-self-intersecting.

Tip: If input areas are self-intersecting, first use the GeometryValidator’s Self-Intersection in 2D rule to remove self-intersections.

Area features resulting from the intersection of input areas are output through this port.

The default behavior is to use the entire set of features as the group. This option allows you to select attributes that define which groups to form.

How parallel processing works with FME: see About Parallel Processing for detailed information.

This parameter determines whether or not the transformer should perform the work across parallel processes. If it is enabled, a process will be launched for each group specified by the Group By parameter.

Parallel Processing Levels

Parameter	Number of Processes
No Parallelism	1
Minimal	coresThe processor, or CPU, is the physical part of the computer that performs mathematical calculations. It is the most important part of a computer system. Traditional processors have only one core on the processor, meaning that at any given time, only one set of calculations is being performed. If a processor is dual-core, this means the single chip contains hardware for two processors, now called cores to distinguish them from the single chip, running simultaneously, side by side. (Source: http://www.ehow.com/facts_5730257_computer-core-processors_.html) / 2
Moderate	exact number of cores
Aggressive	cores x 1.5
Extreme	cores x 2

For example, on a quad-core machine, minimal parallelism will result in two simultaneous FME processes. Extreme parallelism on an 8-core machine would result in 16 simultaneous processes.

You can experiment with this feature and view the information in the Windows Task Manager and the Workbench Log window.

Yes: This transformer will process input groups in order. Changes on the value of the Group By parameter on the input stream will trigger batch processing on the currently accumulating group. This will improve overall speed if groups are large/complex, but could cause undesired behavior if input groups are not truly ordered.

No: This is the default behavior. Processing will only occur in this transformer once all input is present.

The Overlap Count Attribute holds the number of features that the resultant feature overlapped, which will be at least one.

If a List Name is supplied, a list is created of all the attributes of each input area that overlaps the resultant feature.

Note: Attribute lists are not accessible from the output schema in Workbench unless they are first processed using a transformer that operates on them, such as ListExploder or ListConcatenator. All attribute list transformers are displayed in the Contents pane of the Transformer Help under Lists. Alternatively, AttributeExposer can be used.