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Almost all software development revolves around the discovery and use of application programming interfaces (APIs). Once a suitable API is selected, programmers must begin the process of determining what functionality in the API is relevant to a programmer's task and how to use it. Our work aims to understand how API functionality is discovered by programmers and where tooling may be appropriate. We employed a mixed-methods approach to investigate Apache Beam, a distributed data processing API, by mining Beam client code and running a lab study to see how people discover Beam's available functionality. We found that programmers' prior experience with similar APIs significantly impacted their ability to find relevant features in an API and attempting to form a top-down mental model of an API resulted in less discovery of features.