Connects input point features in the order they enter, forming linear or polygonal features.
The output features will contain a merged set of attributes from all the features that were connected together, where the value for an attribute in the resulting feature comes from the first feature that had an attribute with that name that was part of the resulting feature.
For some datasets, it may be necessary to use a Sorter to order the data correctly before it enters this transformer.
If the resulting feature is a single point, it will be output through this port.
If the resulting feature does not begin and end at the same point, it is output through this port.
If the resulting feature forms a ring (begins and ends at the same point), it is output through this port.
Any features that are not points or lines are output through this port.
The default behavior is to use the entire set of input features as the group. This option allows you to select attributes that define which groups to form – each set of features that have the same value for all of these attributes will be processed as an independent group.
If only one point feature was received with a given value for the Group By value, it will be output as a Point.
If the feature output forms a ring (begins and ends at the same point), it is output as a Polygon.
Anything else is output as a Line.
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.
Remove Duplicate Points
If Yes, duplicate coordinates from input features are removed. That is, if two point features, both at (0,0,0) are input, one point at (0,0,0) is output. If No, duplicate coordinates from input features are not removed. That is, if two point features at (0,0,0) are input, a line is output with two coordinates, both at (0,0,0).
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.
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: "point joiner" "line creator" PointConnector