Improving performance in FME by reading data intelligently

This video discusses and demonstrates ways you can improve performance in your FME workspaces by optimizing reading. Techniques include:

- Reordering your readers in the navigator pane
- Dropping unused data as soon as possible in the workflow
- Using parameters to gain more control, and shift expensive operations (e.g. joining) into the database rather than performing them in the middle of the spatial translation
- Using spatial indices and reading within a bounding box
- Removing unneeded features by applying the "Feature Types to Read" parameter and/or applying an SQL 'where' clause within FME
- Synchronous reading/writing, i.e., applying a spatial query mid-translation
- Pre-building database views, i.e., virtual tables, for improved efficiency with repetitive queries

Transformers used: Tester, Clipper, AttributeKeeper, AttributeRemover, SQLCreator, FeatureReader, Joiner, ImageFetcher, RasterReader, HTTPFetcher, InlineQuerier, FeatureMerger

Links from slides: