Combines attributes of the input features into a single list structure.
Example
Suppose this transformer is used with no group-by attributes, and three features enter it with these attributes:
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Feature 0: |
length = 7.3 kind = 'paved' |
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Feature 1: |
length = 8.4 kind = ’smooth’ lanes = 2 |
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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’
Configuration
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
Group Processing (Optional)
| 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. |
| Complete Groups |
When All Features Received: This is the default behavior. Processing will only occur in this transformer once all input is present. 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 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 When All Features Received 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. |
General
|
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. |
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.
Defining Values
There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters. There are a number of tools and shortcuts that can assist in constructing values, generally available from the drop-down context menu adjacent to the value field.
How to Set Parameter Values
Using the Text Editor
The Text Editor provides a convenient way to construct text strings (including regular expressions) from various data sources, such as attributes, parameters, and constants, where the result is used directly inside a parameter.
Using the Arithmetic Editor
The Arithmetic Editor provides a convenient way to construct math expressions from various data sources, such as attributes, parameters, and feature functions, where the result is used directly inside a parameter.
Conditional Values
Set values depending on one or more test conditions that either pass or fail.
Parameter Condition Definition Dialog
Content
Expressions and strings can include a number of functions, characters, parameters, and more.
When setting values - whether entered directly in a parameter or constructed using one of the editors - strings and expressions containing String, Math, Date/Time or FME Feature Functions will have those functions evaluated. Therefore, the names of these functions (in the form @<function_name>) should not be used as literal string values.
Content Types
| These functions manipulate and format strings. | |
|
Special Characters |
A set of control characters is available in the Text Editor. |
| Math functions are available in both editors. | |
| Date/Time Functions | Date and time functions are available in the Text Editor. |
| These operators are available in the Arithmetic Editor. | |
| These return primarily feature-specific values. | |
| FME and workspace-specific parameters may be used. | |
| Creating and Modifying User Parameters | Create your own editable parameters. |
Dialog Options - Tables
Transformers with table-style parameters have additional tools for populating and manipulating values.
Table Tools
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Row Reordering
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Enabled once you have clicked on a row item. Choices include:
|
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Cut, Copy, and Paste
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Enabled once you have clicked on a row item. Choices include:
Cut, copy, and paste may be used within a transformer, or between transformers. |
|
Filter
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Start typing a string, and the matrix will only display rows matching those characters. Searches all columns. This only affects the display of attributes within the transformer - it does not alter which attributes are output. |
|
Import
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Import populates the table with a set of new attributes read from a dataset. Specific application varies between transformers. |
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Reset/Refresh
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Generally resets the table to its initial state, and may provide additional options to remove invalid entries. Behavior varies between transformers. |
Note: Not all tools are available in all transformers.
FME Community
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