Removing the FeatureReader from the BuildingValidator and instead of connecting it to the BuildingValidator with a new Input port results in faster translations.

Removing the FeatureReader from the BuildingValidator and instead of connecting it to the BuildingValidator with a new Input port results in faster translations.

• A. Not sure
• B. N/A
• C. False
• D. True

Answer: (D)

Feeding data into a validator works fastest when you stream features directly from the upstream reader through the validator, without inserting a nested FeatureReader inside the validator. The FeatureReader adds an extra processing layer: it opens and reads a dataset, buffers features, and then passes them along, which introduces overhead and can break streaming efficiency. By removing that inner reader and connecting the upstream reader to the BuildingValidator via a separate input port, the engine can flow features through in a more streamlined, streaming fashion, reducing overhead and often improving throughput. This is especially noticeable with large datasets or complex validation rules, where every extra transform adds up. So, yes, using a direct input port connection typically results in faster translations.

Feeding data into a validator works fastest when you stream features directly from the upstream reader through the validator, without inserting a nested FeatureReader inside the validator. The FeatureReader adds an extra processing layer: it opens and reads a dataset, buffers features, and then passes them along, which introduces overhead and can break streaming efficiency. By removing that inner reader and connecting the upstream reader to the BuildingValidator via a separate input port, the engine can flow features through in a more streamlined, streaming fashion, reducing overhead and often improving throughput. This is especially noticeable with large datasets or complex validation rules, where every extra transform adds up. So, yes, using a direct input port connection typically results in faster translations.