Name
Abstract | ||
|---|---|---|
There has been a recent industrial effort to develop multi-resource hierarchical schedulers. However, the existing implementations have some shortcomings in that they might leave resources unallocated or starve certain jobs. This is because the multi-resource setting introduces new challenges for hierarchical scheduling policies. We provide an algorithm, which we implement in Hadoop, that generalizes the most commonly used multi-resource scheduler, DRF [1], to support hierarchies. Our evaluation shows that our proposed algorithm, H-DRF, avoids the starvation and resource inefficiencies of the existing open-source schedulers and outperforms slot scheduling. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2523616.2523637 | SoCC |
Keywords | Field | DocType |
hierarchical scheduling policy,existing open-source schedulers,existing implementation,diverse datacenter workloads,new challenge,proposed algorithm,certain job,slot scheduling,multi-resource setting,multi-resource hierarchical schedulers,multi-resource scheduler,data center | Multi resource,Scheduling (computing),Computer science,Real-time computing,Implementation,Hierarchy,Data center,Round-robin scheduling,Distributed computing | Conference |
Citations | PageRank | References |
48 | 1.34 | 19 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arka A. Bhattacharya | 1 | 394 | 19.81 |
| David Culler | 2 | 23468 | 2674.49 |
| Eric Friedman | 3 | 739 | 95.62 |
| Ali Ghodsi | 4 | 3306 | 156.01 |
| Scott Shenker | 5 | 29892 | 2677.04 |
| Scott Shenker | 6 | 29892 | 2677.04 |