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Workspace Authoring 101: Feature Caching

Feature Caching is a mode in FME for workspace authoring. It’s basically a way to store data for future access. Feature Caching can save you time and make you more productive – if you know how to use it.

Though not complicated to learn, Feature Caching is often overlooked by FME users because they don't know how to get started. In this webinar, learn the basics of Feature Caching, including:

- Common uses
- Partial runs
- Collapsed bookmarks
- Templates
- And more!

Afterwards, you’ll feel confident using Feature Caching in your workflows and will improve the way you author workflows.

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Workspace Authoring 101: Feature Caching

  1. 1. Workspace Authoring 101: Feature Caching
  2. 2. Meet the Presenter Dave Campanas Applications Expert
  3. 3. Agenda What we’re covering today. ● Why Feature Caching is the coolest thing ever ● When it isn’t so cool
  4. 4. Type in your questions throughout the webinar. It’s also being recorded and a copy of the video, slides, and workspaces will be emailed to you.
  5. 5. Section 1 What is Feature Caching, and how can it help me?
  6. 6. What is Feature Caching ● Stores a copy of the features output for each transformer in workspace ● Workbench setting - is not saved in workspace ● Does not apply when workspace run in Quick Translator, FME Server, or command line FME
  7. 7. Demo
  8. 8. Feature Caching can speed workspace development By reducing the number of times the full workspace must be run, and automating the exposure of new attributes and values.
  9. 9. See the story:
  10. 10. Section 2 When should feature Caching not be used?
  11. 11. Raster workflows ● Rasters are usually quite large ● A copy must cached to disk for each transformer ● FME optimizes raster handling for best performance ● Caching disrupts raster optimization When working with rasters: ● Disable Feature Caching ● Bookmark and collapse raster section in mixed raster/vector workspaces
  12. 12. Workflows using Variables ● VariableSetter and VariableRetriever often used to efficiently transfer information between feature streams and to create lookup tables ● Variables stored in memory and not cached with features ● Variable state lost in partial workspace runs
  13. 13. Workflows where feature order is important ● FeatureMerger, Clipper offer performance options if feature order can be controlled ○ ie. Clippers First option ● Order may not be the same from caches of multiple streams
  14. 14. Resources FME Evangelist Blog, with more examples: Knowledge Article:
  15. 15. Summary Feature Caching can help you develop workspaces faster. Feature Caching should not presently be used when feature order is important, or when variables are used.
  16. 16. Try it Yourself! Download FME 2021.0 Download the workspace from this webinar Apply it to your own data to manage changes Free Trial | Upgrade
  17. 17. Thank you! Get a free trial of FME at Type in your questions for Q&A