Duality-Based Locality-Aware Stream Partitioning in Distributed Stream Processing Engines

被引:0
|
作者
Son, Siwoon [1 ]
Moon, Yang-Sae [1 ]
机构
[1] Kangwon Natl Univ, Chunchon, South Korea
来源
EURO-PAR 2019: PARALLEL PROCESSING WORKSHOPS | 2020年 / 11997卷
关键词
Distributed processing; Data stream; Locality; Duality;
D O I
10.1007/978-3-030-48340-1_57
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose duality-based locality-aware stream partitioning (LSP) in distributed stream processing engines (DSPEs). In general, LSP directly uses the locality concept of distributed batch processing engines (DBPEs). This concept does not fully take into account the characteristics of DSPEs and therefore does not maximize cluster resource utilization. To solve this problem, we first explain the limitations of existing LSP, and we then propose a duality relationship between DBPEs and DSPEs. We finally propose a simple but efficient ping-based mechanism to maximize the locality of DSPEs based on the duality. The insights uncovered in this paper can maximize the throughput and minimize the latency in stream partitioning.
引用
收藏
页码:725 / 730
页数:6
相关论文
共 28 条
  • [1] Locality/Fairness-Aware Job Scheduling in Distributed Stream Processing Engines
    Son, Siwoon
    Moon, Yang-Sae
    ELECTRONICS, 2020, 9 (11) : 1 - 24
  • [2] Stochastic distributed data stream partitioning using task locality: design, implementation, and optimization
    Son, Siwoon
    Im, Hyeonseung
    Moon, Yang-Sae
    JOURNAL OF SUPERCOMPUTING, 2021, 77 (10) : 11353 - 11389
  • [3] Zeus: Locality-aware Distributed Transactions
    Katsarakis, Antonios
    Ma, Yijun
    Tan, Zhaowei
    Bainbridge, Andrew
    Balkwill, Matthew
    Dragojevic, Aleksandar
    Grot, Boris
    Radunovic, Bozidar
    Zhang, Yongguang
    PROCEEDINGS OF THE SIXTEENTH EUROPEAN CONFERENCE ON COMPUTER SYSTEMS (EUROSYS '21), 2021, : 145 - 161
  • [4] Stochastic distributed data stream partitioning using task locality: design, implementation, and optimization
    Siwoon Son
    Hyeonseung Im
    Yang-Sae Moon
    The Journal of Supercomputing, 2021, 77 : 11353 - 11389
  • [5] Locality-Aware Cooperation for VM Scheduling in Distributed Clouds
    Pastor, Jonathan
    Bertier, Marin
    Desprez, Frederic
    Lebre, Adrien
    Quesnel, Flavien
    Tedeschi, Cedric
    EURO-PAR 2014 PARALLEL PROCESSING, 2014, 8632 : 330 - 341
  • [6] SPACE: Locality-Aware Processing in Heterogeneous Memory for Personalized Recommendations
    Kal, Hongju
    Lee, Seokmin
    Ko, Gun
    Ro, Won Woo
    2021 ACM/IEEE 48TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE (ISCA 2021), 2021, : 679 - 691
  • [7] A Distributed Stream Processing based Architecture for IoT Smart Grids Monitoring
    Carvalho, Otavio
    Roloff, Eduardo
    Navaux, Philippe O. A.
    COMPANION PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING (UCC'17 COMPANION), 2017, : 9 - 14
  • [8] TDAG: A Tunable Distributed Data Processing Model for Data Stream
    Tang, Jintao
    Lin, Xuelian
    Shen, Yang
    Wo, Tianyu
    2017 15TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS AND 2017 16TH IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING AND COMMUNICATIONS (ISPA/IUCC 2017), 2017, : 433 - 437
  • [9] An Locality-Aware Scheduling Based on a Novel Scheduling Model to Improve System Throughput of MapReduce Cluster
    Zhao, Hui
    Yang, Shuqiang
    Chen, Zhikun
    Yin, Hong
    Jin, Songchang
    PROCEEDINGS OF 2012 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2012), 2012, : 111 - 115
  • [10] Similarity-based Node Distance Exploring and Locality-aware Shuffle Optimization for Hadoop MapReduce
    Wang, Jihe
    Wang, Danghui
    Zhang, Meng
    Qiu, Meikang
    Guo, Bing
    2017 IEEE INTERNATIONAL CONFERENCE ON SMART CLOUD (SMARTCLOUD), 2017, : 103 - 108