Cache-oblivious scheduling of shared workloads

• Published in: 2015 IEEE 31st International Conference on Data Engineering pp. 855 - 866
• Main Authors: Bar, Arian, Golab, Lukasz, Ruehrup, Stefan, Schiavone, Mirko, Casas, Pedro
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2015
• Subjects: Bandwidth
• ISSN: 1063-6382; 2375-026X
• DOI: 10.1109/ICDE.2015.7113339

Shared workload optimization is feasible if the set of tasks to be executed is known in advance, as is the case in updating a set of materialized views or executing an extract-transform-load workflow. In this paper, we consider data-intensive workloads with precedence constraints arising from data dependencies. While there has been previous work on identifying common subexpressions and task re-ordering to enable shared scans, in this paper we solve the problem of scheduling shared data-intensive workloads in a cache-oblivious way. Our solution relies on a novel formulation of precedence constrained scheduling with the additional constraint that once a data item is in the cache, all tasks that require this item should execute as soon as possible thereafter. We give an optimal algorithm using A* search over the space of possible orderings, and we propose efficient and effective heuristics that obtain nearly-optimal schedules in much less time. We present experimental results on real-life data warehouse workloads and the TCP-DS benchmark to validate our claims.