Elastic online analytical processing on RAMCloud

EDBT '13: Proceedings of the 16th International Conference on Extending Database Technology(2013)

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摘要
A shared-nothing architecture is state-of-the-art for deploying a distributed analytical in-memory database management system: it preserves the in-memory performance advantage by processing data locally on each node but is difficult to scale out. Modern switched fabric communication links such as InfiniBand narrow the performance gap between local and remote DRAM data access to a single order of magnitude. Based on these premises, we introduce a distributed in-memory database architecture that separates the query execution engine and data access: this enables a) the usage of a large-scale DRAM-based storage system such as Stanford's RAMCloud and b) the push-down of bandwidth-intensive database operators into the storage system. We address the resulting challenges such as finding the optimal operator execution strategy and partitioning scheme. We demonstrate that such an architecture delivers both: the elasticity of a shared-storage approach and the performance characteristics of operating on local DRAM.
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关键词
shared-nothing architecture,in-memory database architecture,analytical in-memory database management,elastic online analytical processing,remote dram data access,bandwidth-intensive database operator,performance characteristic,large-scale dram-based storage system,performance gap,data access,in-memory performance advantage,elasticity,performance,analytics
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