Name
Abstract | ||
|---|---|---|
Efficient resource scheduling of multithreaded software on multicore hardware is difficult given the many parameters involved and the hardware heterogeneity of existing systems. In this paper we explore the efficient deployment of query plans over a multicore machine. We focus on shared query systems, and implement the proposed ideas using SharedDB. The goal of the paper is to explore how to deliver maximum performance and predictability, while minimizing resource utilization when deploying query plans on multicore machines. We propose to use resource activity vectors to characterize the behavior of individual database operators. We then present a novel deployment algorithm which uses these vectors together with dataflow information from the query plan to optimally assign relational operators to physical cores. Experiments demonstrate that this approach significantly reduces resource requirements while preserving performance and is robust across different server architectures. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.14778/2735508.2735513 | PVLDB |
Field | DocType | Volume |
Query optimization,Data mining,Software deployment,Computer science,Software,Dataflow,Operator (computer programming),Relational operator,Multi-core processor,Database,Query plan,Distributed computing | Journal | 8 |
Issue | ISSN | Citations |
3 | 2150-8097 | 15 |
PageRank | References | Authors |
0.56 | 35 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jana Giceva | 1 | 108 | 5.08 |
| Gustavo Alonso | 2 | 5476 | 612.79 |
| Timothy Roscoe | 3 | 3118 | 299.48 |
| Tim Harris | 4 | 5393 | 417.21 |