Generating example data for dataflow programs
Christopher Olston, Shubham Chopra, Utkarsh Srivastava · 2009
While developing data-centric programs, users often run (portions of) their programs over real data, to see how they behave and what the output looks like. Doing so makes it easier to formulate, understand and compose programs correctly, compared with examination of program logic alone. For large input data sets, these experimental runs can be time-consuming and inefficient. Unfortunately, sampling the input data does not always work well, because selective operations such as filter and join can lead to empty results over sampled inputs, and unless certain indexes are present there is no way to generate biased samples efficiently. Consequently new methods are needed for generating example input data for data-centric programs.