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TailX: Scheduling Heterogeneous Multiget Queries to Improve Tail Latencies in Key-Value Stores
- Source :
- 20th International Conference on Distributed Applications and Interoperable Systems, 20th International Conference on Distributed Applications and Interoperable Systems, Jun 2020, Valletta, Malta. pp.73-92, ⟨10.1007/978-3-030-50323-9_5⟩, Distributed Applications and Interoperable Systems, Distributed Applications and Interoperable Systems ISBN: 9783030503222, DAIS, Distributed Applications and Interoperable Systems. DAIS 2020, 73-92, STARTPAGE=73;ENDPAGE=92;TITLE=Distributed Applications and Interoperable Systems. DAIS 2020
- Publication Year :
- 2020
- Publisher :
- HAL CCSD, 2020.
-
Abstract
- International audience; Users of interactive services such as e-commerce platforms have high expectations for the performance and responsiveness of these services. Tail latency, denoting the worst service times, contributes greatly to user dissatisfaction and should be minimized. Maintaining low tail latency for interactive services is challenging because a request is not complete until all its operations are completed. The challenge is to identify bottleneck operations and schedule them on uncoordinated backend servers with minimal overhead, when the duration of these operations are heterogeneous and unpredictable. In this paper, we focus on improving the latency of multiget operations in cloud data stores. We present TailX, a task-aware multiget scheduling algorithm that improves tail latencies under heterogeneous workloads. TailX schedules operations according to an estimation of the size of the corresponding data, and allows itself to procrastinate some operations to give way to higher priority ones. We implement TailX in Cassandra, a widely used key-value store. The result is an improved overall performance of the cloud data stores for a wide variety of heterogeneous workloads. Specifically, our experiments under heterogeneous YCSB workloads show that TailX outperforms state-of-the-art solutions and reduces tail latencies by up to 70% and median latencies by up to 75%.
- Subjects :
- 050101 languages & linguistics
Schedule
Computer science
business.industry
Scheduling
Distributed storage
Performance
05 social sciences
Cloud computing
02 engineering and technology
Bottleneck
Article
Scheduling (computing)
[INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF]
Cloud data
Server
Distributed data store
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
0501 psychology and cognitive sciences
[INFO]Computer Science [cs]
Latency (engineering)
[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
business
Computer network
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-030-50322-2
- ISBNs :
- 9783030503222
- Database :
- OpenAIRE
- Journal :
- 20th International Conference on Distributed Applications and Interoperable Systems, 20th International Conference on Distributed Applications and Interoperable Systems, Jun 2020, Valletta, Malta. pp.73-92, ⟨10.1007/978-3-030-50323-9_5⟩, Distributed Applications and Interoperable Systems, Distributed Applications and Interoperable Systems ISBN: 9783030503222, DAIS, Distributed Applications and Interoperable Systems. DAIS 2020, 73-92, STARTPAGE=73;ENDPAGE=92;TITLE=Distributed Applications and Interoperable Systems. DAIS 2020
- Accession number :
- edsair.doi.dedup.....65fd1b780f0c6f228e46454bdd0162be