BoundingBoxAccumulator

One bounding box feature is output for each unique combination of values of the attributes specified in the Group By parameter. The bounding box is the smallest rectangle that contains all the features that were members of the group. If Group By attributes are not specified, a single feature is output that represents the bounding box of all the features.

Process At End (Blocking): This is the default behavior. Processing will only occur in this transformer once all input is present.

Process When Group Changes (Advanced): This transformer will process input groups in order. Changes of the value of the Group By parameter on the input stream will trigger processing on the currently accumulating group. This may improve overall speed (particularly with multiple, equally-sized groups), but could cause undesired behavior if input groups are not truly ordered.

Considerations for Using Group By

There are two typical reasons for using Process When Group Changes (Advanced) . The first is incoming data that is intended to be processed in groups (and is already so ordered). In this case, the structure dictates Group By usage - not performance considerations.

The second possible reason is potential performance gains.

Performance gains are most likely when the data is already sorted (or read using a SQL ORDER BY statement) since less work is required of FME. If the data needs ordering, it can be sorted in the workspace (though the added processing overhead may negate any gains).

Sorting becomes more difficult according to the number of data streams. Multiple streams of data could be almost impossible to sort into the correct order, since all features matching a Group By value need to arrive before any features (of any feature type or dataset) belonging to the next group. In this case, using Group By with Process At End (Blocking) may be the equivalent and simpler approach.

Note: Multiple feature types and features from multiple datasets will not generally naturally occur in the correct order.

As with many scenarios, testing different approaches in your workspace with your data is the only definitive way to identify performance gains.

Specifies how attributes should be accumulated. If Drop Incoming Attributes is selected, all incoming attributes are removed from the features. Merge Incoming Attributes merges all attributes from overlapping features. Use Attributes From One Feature takes all attributes from one representative feature.

Allows you to specify a List Name.

If a List Name is supplied, for each output feature, a list is created of all the attributes of input features that contain the output feature. A list with the same name is created for traits.

Note: List attributes 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. Alternatively, AttributeExposer can be used.

All Attributes: Every attribute from all input features that created an output surface will be added to the list specified in List Name.

Selected Attributes: Only the attributes specified in the Selected Attributes parameter will be added to the list specified in List Name.

The attributes to be added to the list when Add To List is Selected Attributes.