Output Ports
One feature is output for each unique combination of values of the attributes specified in the Group By parameter. Features output from this transformer have no geometry.
Parameters
Transformer
Group By
This parameter allows you to specify the attribute values on which to join the series of input features. One feature is output for each group created by selecting a Group By attribute. If no Group By attributes are specified, then a single feature is output and the number of elements in its list is equivalent to the number of features input into the ListBuilder.
Group By Mode
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.
Parameters
List Name
The features output from the ListBuilder have all of their attributes stored in the list identified by the name specified by this parameter.
Add To List
All Attributes: Every attribute from all input features that created an output feature 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.
Selected Attributes
The attributes to be added to the list when Add To List is Selected Attributes.
Example
Suppose this transformer is used with no group-by attributes, and three features enter it with these attributes:
|
Feature 0: |
length = 7.3 kind = 'paved' |
|
Feature 1: |
length = 8.4 kind = ’smooth’ lanes = 2 |
|
Feature 2: |
length = 1.1 kind = ’rough’ |
then, presuming that the list name specified was somelist, a single feature with these attributes is output:
somelist{0}.length = 7.3
somelist{0}.kind = ’paved’
somelist{1}.length = 8.4
somelist{1}.kind = ’smooth’
somelist{1}.lanes = 2
somelist{2}.length = 1.1
somelist{2}.kind = ’rough’
Editing Transformer Parameters
Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click 
beside the applicable parameter. For more information, see Transformer Parameter Menu Options.
Transformer Categories
FME Community
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