In an FME workflow, which step should generally be used first to improve performance when starting with transformers?

In an FME workflow, which step should generally be used first to improve performance when starting with transformers?

• A. Remove
• B. Action
• C. Filter
• D. Answer

Answer: (C)

Focusing on reducing data as early as possible is the best way to speed up an FME workflow. The Filter transformer is designed to evaluate conditions on each feature and only pass through those that meet the criteria (while routing or discarding the rest). This early pruning cuts the number of features and the amount of geometry processing that downstream, often expensive, transformers must handle, which translates to faster execution and lower memory use. So, when starting with transformers, placing a Filter near the beginning to remove unneeded features is the most effective performance improvement. Other options don’t inherently perform conditional data reduction at the start: removing attributes or features without a condition isn’t the same as filtering by data values, and an Action or a non-transformer option isn’t the same mechanism for pruning the stream.

Focusing on reducing data as early as possible is the best way to speed up an FME workflow. The Filter transformer is designed to evaluate conditions on each feature and only pass through those that meet the criteria (while routing or discarding the rest). This early pruning cuts the number of features and the amount of geometry processing that downstream, often expensive, transformers must handle, which translates to faster execution and lower memory use.

So, when starting with transformers, placing a Filter near the beginning to remove unneeded features is the most effective performance improvement. Other options don’t inherently perform conditional data reduction at the start: removing attributes or features without a condition isn’t the same as filtering by data values, and an Action or a non-transformer option isn’t the same mechanism for pruning the stream.