Common Transformations

Most Valuable Transformers

If you have a thorough understanding of the most common transformers, then you have a good chance of being a very efficient user of FME Workbench.

Anyone can be proficient in FME using only a handful of transformers if they are the right ones!

The Top 30

The list of transformers on the Safe Software website is ordered by most-used, calculated from user feedback. Having this information tells us where to direct our development efforts in making improvements, but it also gives users a head-start on knowing which of the (500+) FME transformers they’re most likely to need in their work.

The following table (last updated March 2019) provides the list of the most commonly used 30 transformers. The Tester transformer is consistently number one in the list every year, highlighting its importance.

Rank Transformer Rank Transformer
1 Tester 16 DuplicateFilter
2 AttributeCreator 17 FeatureReader
3 AttributeManager 18 StringReplacer
4 FeatureMerger 19 VertexCreator
5 Inspector 20 StatisticsCalculator
6 AttributeKeeper 21 SpatialFilter
7 TestFilter 22 Sorter
8 Creator 23 AttributeExposer
9 AttributeRenamer 24 Bufferer
10 Reprojector 25 Dissolver
11 Aggregator 26 GeometryFilter
12 AttributeRemover 27 ListExploder
13 AttributeFilter 28 FeatureJoiner
14 Clipper 29 AttributeSplitter
15 Counter 30 CoordinateExtractor

Categories

Besides the obvious transformers for transforming geometry (Clipper, Bufferer, Dissolver) and the obvious transformers for transforming attribute values (StringReplacer, Counter) there are some other distinct groups of transformers.

Managing Attributes

These transformers - mostly named the Attribute<Something> - are primarily for managing attributes (creating, renaming, and deleting) for schema mapping purposes. However, they can also be used to set new attribute values or update existing ones.

Filtering

These transformers - mostly named the <Something>Filter - subdivide data as it flows through a workspace. Commonly the filter is a conditional filter, where features are output according to the results of a test or condition.

Data Joins

Joins are the opposite action to filtering; they are when separate streams of data are combined as they flow through a workspace. Like filtering, there is a condition to be met - in this case matching key values - that determines how and where the join takes place.

FME is Broad

FME has an extensive scope. It can connect to hundreds of formats and has hundreds of transformers. Some users only use one format and a handful of transformers, while others use many more. All of these are valid ways to use FME. Do not be worried if you feel overwhelmed at first; many users do! Through completing training, you will learn about a few essential transformers. After that, we have a plethora of resources to help you learn about more formats and transformations:

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