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 25

The list of transformers on the Safe Software web site 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 (400+) FME transformers they’re most likely to need in their work.

The following table (last updated August 2017) provides the list of the most commonly used 25 transformers. The Tester transformer is consistently number one in the list every year, highlighting its importance.

Rank Transformer Rank Transformer
1Tester2AttributeCreator
3AttributeManager4FeatureMerger
5Creator6Inspector
7AttributeKeeper8TestFilter
9Clipper10Reprojector
11AttributeRenamer12Aggregator
13FeatureReader14AttributeFilter
15VertexCreator16AttributeRemover
17StringReplacer18Counter
19Bufferer20StatisticsCalculator
21SpatialFilter22GeometryFilter
23AttributeExposer24Sorter
25Dissolver

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.

TIP
The AttributeManager is a multi-purpose transformer for carrying out most attribute-related functionality. It is slowly rising up the list, above transformers it replaces, like the AttributeRemover and AttributeRenamer.

Filtering

These transformers - mostly named the <Something>Filter - subdivide data as it flows through a workspace. Commonly the filter is a conditional filter, where the decision about which features are output to which connection is decided by some form of 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 determine how and where the join takes place.

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