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Toward Massive Query Optimization in Large-Scale Distributed Stream Systems

Summary: Toward Massive Query Optimization in
Large-Scale Distributed Stream Systems
Yongluan Zhou1
, Karl Aberer2
, and Kian-Lee Tan3,
University of Southern Denmark
EPFL, Switzerland
National University of Singapore
Abstract. Existing distributed stream systems adopt a tightly-coupled
communication paradigm and focus on fine-tuning of operator place-
ments to achieve communication efficiency. This kind of approach is hard
to scale (both to the nodes in the network and the users). In this paper,
we propose a fundamentally different approach and present the design
of a middleware for optimizing massive queries. Our approach takes the
advantages of existing Publish/Subscribe systems (Pub/Sub) to achieve
loosely-coupled communication and to "intelligently" exploit the sharing
of communication among different queries. To fully exploit the capability


Source: Aberer, Karl - Faculté Informatique et Communications, Ecole Polytechnique Fédérale de Lausanne


Collections: Computer Technologies and Information Sciences