Jules S. Damji in a quick intro to Cascading:
At the core of most data-driven applications is a data pipeline through
which data flows, originating from Taps and Sources (ingestion) and ending
in a Sink (retention) while undergoing transformation along a pipeline
(Pipes, Traps, and Flows). And should something fail, a Trap (exception)
must handle it. In the big data parlance, these are aspects of ETL
You have to agree that when compared with the MapReduce model, these components could bring a lot of readability to your code. On the other hand, at a first glance Cascading API still feels verbose.
Original title and link: Cascading components for a Big Data applications