Optimization for Speculative Execution in Big Data Processing Clusters

A big parallel processing job can be delayed substantially as long as one of its many tasks is being assigned to an unreliable or congested machine. To tackle this so-called straggler problem, most parallel processing frameworks such as MapReduce have adopted various strategies under which the syste...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems 2017-02, Vol.28 (2), p.530-545
Hauptverfasser:	Xu, Huanle, Lau, Wing Cheong
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Big data Central processing units Cloning Clustering algorithms Clusters Computer simulation CPUs Data management Data processing Hierarchies Job scheduling Job shop scheduling Optimization Parallel processing Resource scheduling Response time Servers speculative execution straggler detection
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