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Paper detail

Towards a Workload for Evolutionary Analytics

Emerging data analysis involves the ingestion and exploration of new data sets, application of complex functions, and frequent query revisions based on observing prior query answers. We call this new type of analysis evolutionary analytics and identify its properties. This type of analysis is not well represented by current benchmark workloads. In this paper, we present a workload and identify several metrics to test system support for evolutionary analytics. Along with our metrics, we present methodologies for running the workload that capture this analytical scenario.

preprint2013arXivOpen access
Jeff LeFevreJagan SankaranarayananHakan HacigumusJunichi TatemuraNeoklis Polyzotis
PerformanceDatabasesDistributed, Parallel, and Cluster Computing
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Jeff LeFevreJagan SankaranarayananHakan HacigumusJunichi TatemuraNeoklis Polyzotis

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