How many features belong to the Mount Pleasant reader feature type?

How many features belong to the Mount Pleasant reader feature type?

• A. 16
• B. 12
• C. 13
• D. 114

Answer: (A)

In a reader in FME, a feature type represents the collection of features that come from one source dataset. The number of features belonging to that reader feature type is simply how many individual records exist in that source for that type. For the Mount Pleasant dataset, there are 16 such features, so 16 is the correct count. You can verify this by inspecting the source data or by using a simple counter in your workspace to tally features as they stream through the Mount Pleasant reader feature type. The other numbers don’t match the actual feature count in that dataset, which is why they aren’t correct.

In a reader in FME, a feature type represents the collection of features that come from one source dataset. The number of features belonging to that reader feature type is simply how many individual records exist in that source for that type. For the Mount Pleasant dataset, there are 16 such features, so 16 is the correct count. You can verify this by inspecting the source data or by using a simple counter in your workspace to tally features as they stream through the Mount Pleasant reader feature type. The other numbers don’t match the actual feature count in that dataset, which is why they aren’t correct.