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Sampler

Preserves either a total number of features or a sampling of features, depending on the Sampling Type selection. The remainder of the input features are output through the NotSampled port.

This transformer is typically used during testing to reduce data volume by arbitrarily discarding data.

Output Ports

ClosedSampled

Preserved features are output through this port.

ClosedNotSampled

Features that are not preserved are output through this port.

Parameters

ClosedGroup By

When specified, this parameter affects the behavior of the sampling types. For example, say the Sampler receives a set of 15 features. Using the Group By parameter, the Sampler breaks the features into 3 groups.

  • Group 1 has 3 features
  • Group 2 has 5 features
  • Group 3 has 7 features

This table shows how sampling amount and type affect the Group By results:

Sampling Amount Sampling Type Result
4 Every Nth Feature
  • 0 features from Group 1 will be sampled
  • 1 feature from Group 2 will be sampled: the 4th feature
  • 1 feature from Group 3 will be sampled: the 4th feature
4 First N Features
  • 3 features from Group 1 will be sampled
  • 4 features from Group 2 will be sampled: the first 4 features
  • 4 features from Group 3 will be sampled: the first 4 features
4 Last N Features
  • 3 features from Group 1 will be sampled
  • 4 features from Group 2 will be sampled: the last 4 features
  • 4 features from Group 3 will be sampled: the last 4 features
ClosedSampling Rate (N)/Sampling Type

Determines the number of features to send to the Sampled port: either a total number of features, or a sampling of features.

If the Sampling Rate (N) is 0, all input data will be sent to the NotSampled port.

For example:

Sampling Rate Sampling Type Result
1 Every Nth Feature Every feature will be sampled.
2 Every Nth Feature Every second feature will be sampled.
10 First N Features Only the first 10 features will be sampled. All subsequent features will be sent to the NotSampled port.
10 Last N Features Only the last 10 features will be sampled. All earlier features will be sent to the NotSampled port.
ClosedRandomize Sampling

When this parameter is left at the default setting of No, the transformer works with features in the order in which they are received.

If this parameter is Yes, the input features are shuffled before they are sampled. All features are blocked in the Sampler until the last feature arrives. The output ports will return the features in the original order they were received by this transformer.

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.

Transformer Categories

Data Quality

Filters and Joins

Workflows

Technical History

Associated FME function or factory: SamplingFactory

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