Musketeer
Ionel Gog, Malte Schwarzkopf, Natacha Crooks, Matthew P. Grosvenor, Allen Clement, Steven J. Hand · 2015
Many systems for the parallel processing of big data are available today. Yet, few users can tell by intuition which system, or combination of systems, is "best" for a given workflow. Porting workflows between systems is tedious. Hence, users become "locked in", despite faster or more efficient systems being available. This is a direct consequence of the tight coupling between user-facing front-ends that express workflows (e.g., Hive, SparkSQL, Lindi, GraphLINQ) and the back-end execution engines that run them (e.g., MapReduce, Spark, PowerGraph, Naiad).