Document Type dissertation Author Name Wang, Song URN etd-032508-044505 Title State-Slice: A New Stream Query Optimization Paradigm for Multi-query and Distributed Processing Degree PhD Department Computer Science Advisors Elke A. Rundensteiner, Advisor Murali Mani, Committee Member George Heineman, Committee Member Ugur Cetintemel, Committee Member Michael Gennert, Department Head Keywords database optimization stream query processing Date of Presentation/Defense 2008-03-17 Availability unrestricted
Modern stream applications necessitate the handling of large numbers of continuous queries specified over high volume data streams. This dissertation proposes novel solutions to continuous query optimization in three core areas of stream query processing, namely state-slice based multiple continuous query sharing, ring-based multi-way join query distribution and scalable distributed multi-query optimization.
The first part of the dissertation proposes efficient optimization strategies that utilize the novel state-slicing concept to achieve maximum memory and computation sharing for stream join queries with window constraints. Extensive analytical and experimental evaluations demonstrate that our proposed strategies is capable to minimize the memory or CPU consumptions for multiple join queries.
The second part of this dissertation proposes a novel scheme for the distributed execution of generic multi-way joins with window constraints. The proposed scheme partitions the states into disjoint slices in the time domain, and then distributes the fine-grained states in the cluster, forming a virtual computation ring. New challenges to support this distributed state-slicing processing are answered by numerous new techniques. The extensive experimental evaluations show that the proposed strategies achieve significant performance improvements in terms of response time and memory usages for a wide range of configurations and workloads on a real system.
Ring based distributed stream query processing and multi-query sharing both are based on the state-slice concept. The third part of this dissertation combines the first two parts of this dissertation work and proposes a novel distributed multi-query optimization technique.
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