Partitioning functions for stateful data parallelism in stream processing

@article{Gedik2013PartitioningFF,
  title={Partitioning functions for stateful data parallelism in stream processing},
  author={Bugra Gedik},
  journal={The VLDB Journal},
  year={2013},
  volume={23},
  pages={517-539}
}
In this paper, we study partitioning functions for stream processing systems that employ stateful data parallelism to improve application throughput. In particular, we develop partitioning functions that are effective under workloads where the domain of the partitioning key is large and its value distribution is skewed. We define various desirable properties for partitioning functions, ranging from balance properties such as memory, processing, and communication balance, structural properties… CONTINUE READING
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