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Custom Transformer Parameters

When you open a custom transformer, a Transformer Parameters node appears in the Workbench Navigator. This node contains parameters that are common to all custom transformers.

ClosedName

Name of the custom transformer

ClosedPassword

If a custom transformer is exported, it can be password-protected. For more information, see Workspace Parameters.

ClosedTransformer Insert Mode

Determines how the transformer is referenced in workspaces. May depend on whether the transformer is exported or not.

ClosedDeprecated

If Yes, the transformer is no longer available for use in newly-created workspaces. It remains usable only in existing workspaces.

ClosedParallel Processing

Specifies the number of threads the custom transformer can process in parallel.

Level Number of Processes
No Parallelism 1
Minimal Cores / 2
Moderate Exact number of cores
Aggressive Cores * 1.5
Extreme Cores * 2

For more information, see Custom Transformers and Parallel Processing.

ClosedGroup By

Specifies an attribute or parameter by which to group parallel processing threads. For example, if the attribute 'STATE' is specified, the transformer processes each state in parallel.

ClosedGroup By Mode

If Input Ordered by Group, the FME engine can assume that data is inputted to the custom transformer in order for each Group By parameter value. This setting provides a performance and memory boost, because the engine does not need to wait for all features to arrive before beginning a process. Set this value to Input Ordered by Group only if the structure of your dataset allows for data throughput in order by the Group By setting.

ClosedDescription

For information about Description parameters, see Workspace Parameters.

ClosedAdvanced

Enable  Blocked Looping

If Yes, the transformer can bypass its blocking behavior when used in a loop, and the following additional parameters apply:

  • Maximum number of iterations
  • Atttribute to hold iteration count

For more information, see Looping with a Blocking Transformer.

Incoming Attribute Preservation

Use this parameter to optimize performance by controlling how workbench determines the output of attributes that enter the custom transformer. If you already know all incoming attributes either pass through or are dropped by the custom transformer, the All Attributes or Drop Attributes settings, respectively, allow workbench to avoid the calculations that are otherwise necessary to achieve the same results.

  • Automatic: Workbench determines which incoming attributes are output by each port.
  • All Attributes: Instructs workbench to pass through all incoming attributes to all output ports. Use this setting if you already know the custom transformer performs in this manner.
  • Drop Attributes: Instructs workbench to eliminate all incoming attributes (that is, no incoming attributes are output). Use this setting if you already know the custom transformer performs in this manner, or you do not need workbench to provide a final display of output attributes.
ClosedScripting

Python Compatibility

See Python Compatibility.