Adaptive scheduling for shared window joins over data streams

作者：Jin Cheqing; Zhou Aoying^*; Yu Jeffrey Xu; Huang Joshua Zhexue; Cao Feng

来源：Frontiers of Computer Science in China, 2007, 1(4): 468-477.

DOI：10.1007/s11704-007-0046-8

• Adaptive scheduling
• Adaptive strategies
• Continuous datums
• Continuous queries
• Continuous query
• Data streams
• Experimental evaluations
• Multiple queries
• New strategies
• Realtime informations
• Scheduling strategies
• Shared window joins
• Static informations
• Window joins

Recently a few Continuous Query systems have been developed to cope with applications involving continuous data streams. At the same time, numerous algorithms are proposed for better performance. A recent work on this subject was to define scheduling strategies on shared window joins over data streams from multiple query expressions. In these strategies, a tuple with the highest priority is selected to process from multiple candidates. However, the performance of these static strategies is deeply influenced when data are bursting, because the priority is determined only by static information, such as the query windows, arriving order, etc. In this paper, we propose a novel adaptive strategy where the priority of a tuple is integrated with realtime information. A thorough experimental evaluation has demonstrated that this new strategy can outperform the existing strategies.

• 出版日期2007
• 单位IBM