2DGridAccumulator

This transformer accepts any feature.

The grid of point or polygon features covering the bounding box area of the input features.

Features with non-numeric attributes for Column Width and Row Height or Number of Horizontal Tiles and Number of Vertical Tiles are output through this port. However, once a feature with numeric values in these attributes is received, all following features will use these same attribute values and will not be rejected.

Rejected features will have an fme_rejection_code attribute with one of the following values: INVALID_GEOMETRY_TYPE, INVALID_PARAMETER_SURFACE_NORMAL_DEVIATION, INVALID_PARAMETER_THICKNESS.

The input features may be partitioned into groups based on attribute values and one bounding box feature is output for each group. If you do not specify any Group By attributes, all input features will be processed together and a single bounding box will be output.

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.

Specifies how the grid size will be defined. Cell Size will enable the Column Width and Row Height parameters, while Number of Cells will enable the Number of Horizontal/Vertical Tiles parameters.

Chooses a starting corner for the purposes of numbering rows and columns. Also, when Grid Type is Cell Size, the last row and/or the last column may extend beyond the bounds of the input features; here the “last” row or column is the one opposite the Starting Corner.

Choose point or polygon features.

Choosing Polygons will generate rectangular boxes with the specified column width and row height.

If Points (Corners) is selected, the corners of all the rectangles in the grid will be output. Points (Centers) will generate the middle point of each rectangle.

Note that there will be more features output for Points (Corners) than for either of Polygons and Points (Centers), since there will be one additional row and one additional column.

The Column Width and Row Height parameters specify in ground units the distance between output points in the grid or the width and height of the output polygons.

Important: If you use attribute values as the Column Width and/or Row Height, only the attributes of the first encountered feature of each group are used. These attributes will be ignored for any following features from the same group.

These optional parameters specify a "seed point" from which cells will be generated. Note that it is permissible to specify a value for only one of these parameters—not necessarily both.

The Number of Horizontal Tiles and Number of Vertical Tiles parameters are required when the Grid Type parameter is Number of Cells, and allow you to specify how to tile the input data (for example, 5 horizontal tiles and 5 vertical tiles).

Important: If you use attribute values as the Number of Horizontal Tiles and/or Number of Vertical Tiles, only the attributes of the first encountered feature of each group are used. These attributes will be ignored for any following features from the same group.

If Column Attribute or Row Attribute are specified, attributes will be added to each output tile that identify the position of that tile in the input raster. These indices are zero-based, beginning at the specified Starting Corner.

If Column Attribute or Row Attribute are specified, attributes will be added to each output tile that identify the position of that tile in the input raster. These indices are zero-based, beginning at the specified Starting Corner.