Title page for ETD etd-032508-044505

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

Abstract
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.

Files
swang.pdf

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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
Abstract 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.
Files	swang.pdf