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In the last few years, the concept of data lake has become trendy for datastorage and analysis. Thus, several design alternatives have been proposed tobuild data lake systems. However, these proposals are difficult to evaluate asthere are no commonly shared criteria for comparing data lake systems. Thus, weintroduce DLBench, a benchmark to evaluate and compare data lakeimplementations that support textual and/or tabular contents. More concretely,we propose a data model made of both textual and raw tabular documents, aworkload model composed of a set of various tasks, as well as a set ofperformance-based metrics, all relevant to the context of data lakes. As aproof of concept, we use DLBench to evaluate an open source data lake system wepreviously developed.

Benchmarking Data Lakes Featuring Structured and Unstructured Data with DLBench