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The availability of large number of processing nodes in a parallel anddistributed computing environment enables sophisticated real time processingover high speed data streams, as required by many emerging applications.Sliding window stream joins are among the most important operators in a streamprocessing system. In this paper, we consider the issue of parallelizing asliding window stream join operator over a shared nothing cluster. We propose aframework, based on fixed or predefined communication pattern, to distributethe join processing loads over the shared-nothing cluster. We consider variousoverheads while scaling over a large number of nodes, and propose solutionmethodologies to cope with the issues. We implement the algorithm over acluster using a message passing system, and present the experimental resultsshowing the effectiveness of the join processing algorithm.

Parallelizing Windowed Stream Joins in a Shared-Nothing Cluster