AnchoredSnapper

Features that may have Candidate features snapped to them. Arcs are snapped as linear features, and ellipses are snapped as polygonal features.

Features that may be snapped to Anchor features. Arcs are snapped as linear features, and ellipses are snapped as polygonal features.

Candidates whose geometry is changed by the transformer.

Candidates that leave the transformer without being changed.

• If a line or area feature snaps down to a single location, it will be output as a Point geometry, through the Collapsed port.
• If an Aggregate, MultiArea, or MultiCurve geometry has any parts snap down to a single location, a Point geometry for each part will be bundled up into a MultiPoint geometry and output through the Collapsed port. The remaining parts which did not snap down to a single location (if any) will be output as a group through the Snapped port.

The anchors that were used during snapping. If a candidate was snapped to a point along the segment of an anchor, a new node is inserted into the anchor’s geometry.

If you select Group By attributes, only those features with the same Group By attribute values will be snapped together.

Note: How parallel processing works with FME: see About Parallel Processing for detailed information.

This parameter determines whether or not the transformer should perform the work across parallel processes. If it is enabled, a process will be launched for each group specified by the Group By parameter.

Parallel Processing Levels

For example, on a quad-core machine, minimal parallelism will result in two simultaneous FME processes. Extreme parallelism on an 8-core machine would result in 16 simultaneous processes.

You can experiment with this feature and view the information in the Windows Task Manager and the Workbench Log window.

No: This is the default behavior. Processing will only occur in this transformer once all input is present.

By Group: This transformer will process input groups in order. Changes of the value of the Group By parameter on the input stream will trigger batch processing on the currently accumulating group. This will improve overall speed if groups are large/complex, but could cause undesired behavior if input groups are not truly ordered.

Considerations for Using Input is Ordered By

Using Ordered input can provide performance gains in some scenarios, however, it is not always preferable, or even possible. Consider the following when using it, with both one- and two-input transformers.

Single Datasets/Feature Types: Are generally the optimal candidates for Ordered processing. If you know that the dataset is correctly ordered by the Group By attribute, using Input is Ordered By can improve performance, depending on the size and complexity of the data.

If the input is coming from a database, using ORDER BY in a SQL statement to have the database pre-order the data can be an extremely effective way to improve performance. Consider using a Database Readers with a SQL statement, or the SQLCreator transformer.

Multiple Datasets/Feature Types: 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, using Ordering with multiple feature types is more complicated than processing a single feature type.

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

One approach is to send all features through a Sorter, sorting on the expected Group By attribute. The Sorter is a feature-holding transformer, collecting all input features, performing the sort, and then releasing them all. They can then be sent through an appropriate filter (TestFilter, AttributeFilter, GeometryFilter, or others), which are not feature-holding, and will release the features one at a time to the transformer using Input is Ordered By, now in the expected order.

The processing overhead of sorting and filtering may negate the performance gains you will get from using Input is Ordered By. In this case, using Group By without using Input is Ordered By may be the equivalent and simpler approach.

In all cases when using Input is Ordered By, if you are not sure that the incoming features are properly ordered, they should be sorted (if a single feature type), or sorted and then filtered (for more than one feature or geometry type).

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

When Snapping Type is End Point Snapping:

• The transformer snaps endpoints of features that enter via the Candidate port to endpoints of features that enter via the Anchor port. Anchor features are not output.
• Point features can be used as Anchor or Candidate features, and Candidate points will be snapped together (or to a linear base feature) as well.
• The transformer will not alter area features.

When Snapping Type is Vertex Snapping:

• The transformer snaps vertices of features that enter via the Candidate port to vertices of features that enter via the Anchor port. Anchor features are not output.
• Point features can be used as Anchor or Candidate features, and Candidate points will be snapped together (or to a linear Anchor feature) as well.
• The transformer will alter area features.

When this parameter is set to Segment Snapping:

• The transformer snaps vertices of curves or points that enter via the Candidate port to lines of features that enter via the Anchor port, if their distances are within the specified tolerance. Anchor features are not output.
• The transformer snaps vertices of Candidate segments to Anchor segments if their distances are within the specified tolerance at any point along the segment.
• Candidate segments which cross Anchor segments will have new vertices introduced at the point of intersection, but the Candidate segments will not be split.
• Segment snapping may cause duplicate points, where segments have degenerated to a point.
• Area features are altered by this operation as its vertices and segments are snapped.

Snapping Distance specifies the distance, in ground units, that the snapping occurs between features.

When Snapping Type is Segment Snapping, this transformer performs data cleaning that is meant to improve the robustness of the results when they are used in other algorithms by ensuring that no two vertices in the snapped output are within tolerance of each other.

If Tolerance is set to Automatic, a tolerance will automatically be calculated for the cleaning operation, based on the size of the inputs. Otherwise, a custom tolerance may be used.

This parameter applies only when the end point of a feature is being snapped.

• NEVER: the endpoint of a line is moved when it is snapped and no additional vertex is added.
• ALWAYS: the original end point (start point) of the line becomes the second from the end (start) and a new vertex is added to complete the snap.
• FORWARD_ONLY: a new vertex is added only when doing so creates an angle greater than 90 degrees with the original line segment. In this case, if adding the vertex would cause a less than 90-degree angle, the old end point is still moved.