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Optimizing data aggregation for cluster-based internet services
2003
Proceedings of the ninth ACM SIGPLAN symposium on Principles and practice of parallel programming - PPoPP '03
Large-scale cluster-based Internet services often host partitioned datasets to provide incremental scalability. The aggregation of results produced from multiple partitions is a fundamental building block for the delivery of these services. This paper presents the design and implementation of a programming primitive -Data Aggregation Call (DAC) -to exploit partition parallelism for clusterbased Internet services. A DAC request specifies a local processing operator and a global reduction
doi:10.1145/781498.781517
dblp:conf/ppopp/ChuTYS03
fatcat:ykr5yvvkg5hyhoh6cu4eqewstu