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There is a growing trend of performing analysis on large datasets usingworkflows composed of MapReduce jobs connected through producer-consumerrelationships based on data. This trend has spurred the development of a numberof interfaces--ranging from program-based to query-based interfaces--forgenerating MapReduce workflows. Studies have shown that the gap in performancecan be quite large between optimized and unoptimized workflows. However,automatic cost-based optimization of MapReduce workflows remains a challengedue to the multitude of interfaces, large size of the execution plan space, andthe frequent unavailability of all types of information needed foroptimization. We introduce a comprehensive plan space for MapReduce workflowsgenerated by popular workflow generators. We then propose Stubby, a cost-basedoptimizer that searches selectively through the subspace of the full plan spacethat can be enumerated correctly and costed based on the information availablein any given setting. Stubby enumerates the plan space based on plan-to-plantransformations and an efficient search algorithm. Stubby is designed to beextensible to new interfaces and new types of optimizations, which is adesirable feature given how rapidly MapReduce systems are evolving. Stubby'sefficiency and effectiveness have been evaluated using representative workflowsfrom many domains.

Stubby: A Transformation-based Optimizer for MapReduce Workflows