Resource Efficient Stream Processing Platform with Latency-Aware Scheduling Algorithms

Authors: 

Yuta Morisawa, Masaki Suzuki, and Takeshi Kitahara, KDDI Research, Inc.

Abstract: 

We presented a novel platform dedicated to stream processing that improved resource efficiency by sharing resources among applications. The platform utilized latency-aware schedulers to handle stream applications with heterogeneous SLAs and workloads. We implemented the prototype in Spark Structured Streaming and evaluated the platform with pseudo IoT services. The result showed that our platform outperformed default Spark Structured Streaming while reducing the necessary CPU cores by 36%. We further compared the adaptability of the schedulers and found that one of the schedulers reduced the SLA violations by 90% compared to the default FAIR when the platform was overloaded.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@inproceedings {254130,
author = {Yuta Morisawa and Masaki Suzuki and Takeshi Kitahara},
title = {Resource Efficient Stream Processing Platform with Latency-Aware Scheduling Algorithms},
booktitle = {12th {USENIX} Workshop on Hot Topics in Cloud Computing (HotCloud 20)},
year = {2020},
url = {https://www.usenix.org/conference/hotcloud20/presentation/morisawa},
publisher = {{USENIX} Association},
month = jul,
}

Presentation Video