Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters

@inproceedings{Karanasos2015MercuryHC,
  title={Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters},
  author={Konstantinos Karanasos and Sriram Rao and Carlo Curino and Chris Douglas and Kishore Chaliparambil and Giovanni Matteo Fumarola and Solom Heddaya and Raghu Ramakrishnan and Sarvesh Sakalanaga},
  booktitle={USENIX Annual Technical Conference},
  year={2015}
}
Datacenter-scale computing for analytics workloads is increasingly common. High operational costs force heterogeneous applications to share cluster resources for achieving economy of scale. Scheduling such large and diverse workloads is inherently hard, and existing approaches tackle this in two alternative ways: 1) centralized solutions offer strict, secure enforcement of scheduling invariants (e.g., fairness, capacity) for heterogeneous applications, 2) distributed solutions offer scalable… CONTINUE READING
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