Creates aggregates of features based on their proximity to each other. Each aggregate that is created covers approximately the neighborhood width and height (measured in feature ground units).
This transformer is used to reduce the data volume of "wallpaper" types of features that have no individual attributes. The resulting aggregates can be output to a system using many fewer records than if each feature was output by itself. For systems that support aggregates, or multi-part features, this can result in substantial performance improvements and greatly decrease storage requirements.
If you do not select Group By attributes, then all features fall into the same group.
When you select Group By attributes, this transformer will aggregate the geometries of the input features, based on the selection in the Group By parameter. Each group of features that have the same values for the Group By attributes will be processed independently of other groups.
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.
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.
These parameters, measured in ground units, divide the input space into cells. The result is a grid of cells that expands in all directions from the origin (0,0). The center of the bounding box of each input feature is used to determine the cell for the feature. Once all input features have been read, an aggregate feature is created from all features in each cell. If linear features are input, they will have pseudo nodes removed from within their cells to further reduce the number of separate entities. No such reduction is done to any polygons or donuts that enter.
Note: To view the grid of cells that is created from these parameters, use the 2DGridCreator. Specify 0,0 for Starting X Coordinate and Starting Y Coordinate, respectively, and the same values for Column Width and Row Height as Neighborhood Width and Neighborhood Height, respectively.
When you set this parameter, neighborhoods with fewer than the specified number of features are merged with a vertical neighbor area in order to increase the number of members. You can prevent this from happening by setting the parameter to 0 (zero).
If Drop Incoming Attributes is chosen, the output feature will not preserve any input attributes. If Merge Incoming Attributes is chosen, the output feature will merge all input attributes. If Use Attributes From One Feature is chosen, the output feature will get attributes from only one input feature.
If a List Name is specified, then all attributes of an input feature will be stored as part of a list attribute entry in the output feature.
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 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.
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.
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.
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.
Set values depending on one or more test conditions that either pass or fail.
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.
|These functions manipulate and format strings.|
|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.
Enabled once you have clicked on a row item. Choices include:
Cut, Copy, and Paste
Enabled once you have clicked on a row item. Choices include:
Cut, copy, and paste may be used within a transformer, or between transformers.
|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 populates the table with a set of new attributes read from a dataset. Specific application varies between transformers.|
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.
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Keywords: MBR "minimum bounding rectangle" Clumper NeighbourhoodAggregator