What transformer can you use to get around the fact you cannot include readers in custom transformers?

What transformer can you use to get around the fact you cannot include readers in custom transformers?

• A. AttributeCreator
• B. FeatureReader
• C. Creator
• D. FeatureWriter

Answer: (B)

In FME, custom transformers can’t embed Reader transformers directly, so you need a way to bring external data into the inside network without adding a Reader there. The FeatureReader is designed for this: it acts as a data source inside the custom transformer, reading from an external dataset and feeding those features into the transformer as if the data were read at workspace level. This lets you parameterize the source and reuse the transformer while still accessing the necessary input data. AttributeCreator only makes new fields, not read data. Creator generates initial features when there’s no input. FeatureWriter writes data out to a dataset, not read from it. So none of those provide a data source inside the custom transformer, whereas FeatureReader does.

In FME, custom transformers can’t embed Reader transformers directly, so you need a way to bring external data into the inside network without adding a Reader there. The FeatureReader is designed for this: it acts as a data source inside the custom transformer, reading from an external dataset and feeding those features into the transformer as if the data were read at workspace level. This lets you parameterize the source and reuse the transformer while still accessing the necessary input data.

AttributeCreator only makes new fields, not read data. Creator generates initial features when there’s no input. FeatureWriter writes data out to a dataset, not read from it. So none of those provide a data source inside the custom transformer, whereas FeatureReader does.