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Scalable transaction processing through dataoriented execution: OLTP on highly parallel hardware with DORA,Used
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Data management technology changes the world we live in by providing efficient access to huge volumes of constantly changing data and by enabling sophisticated analysis of those data. In parallel, we witness a tremendous shift in the underlying hardware technology toward highly parallel multicore processors. Data management systems need to fully exploit the abundantly available hardware parallelism. Transaction processing is one of the most important and challenging database workloads and this dissertation contributes to the quest for scalable transaction processing software. It shows that conventional transaction processing has inherent scalability limitations due to the unpredictable access patterns caused by the requestoriented execution model it follows. Instead, it proposes adopting a dataoriented execution model, and shows that transaction processing systems designed around dataoriented execution break the inherent limitations of conventional execution. The dataoriented design paves the way for transaction processing systems to maintain scalability as parallelism increases for the foreseeable future; as hardware parallelism increases, the benefits will only increase.
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