ImRP: A Predictive Partition Method for Data Skew Alleviation in Spark Streaming Environment

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成果类型：

期刊论文

作者：

Fu, Zhongming;Tang, Zhuo*;Yang, Li;Li, Kenli;Li, Keqin

通讯作者：

Tang, Zhuo

作者机构：

[Li, Kenli; Fu, Zhongming; Tang, Zhuo] Hunan Univ, Coll Informat Sci & Engn, Changsha, Hunan, Peoples R China.

[Li, Kenli; Fu, Zhongming; Tang, Zhuo] Natl Supercomp Ctr Changsha, Changsha, Hunan, Peoples R China.

[Fu, Zhongming] Univ South China, Coll Comp Sci & Technol, Hengyang, Peoples R China.

[Yang, Li] Changsha Univ Sci & Technol, Coll Comp & Commun Engn, Changsha, Hunan, Peoples R China.

[Li, Keqin] SUNY Coll New Paltz, Dept Comp Sci, New Paltz, NY 12561 USA.

通讯机构：

[Tang, Zhuo] H

[Tang, Zhuo] N

Hunan Univ, Coll Informat Sci & Engn, Changsha, Hunan, Peoples R China.

Natl Supercomp Ctr Changsha, Changsha, Hunan, Peoples R China.

语种：

英文

关键词：

Balancing;Benchmarking;Data streams;Predictive analytics;Semantics;Computing environments;Data distribution;Exponentially weighted moving average;High throughput;Job performance;Partition methods;Prediction model;Stream processing;Batch data processing

期刊：

Parallel Computing

ISSN：

0167-8191

年：

2020

卷：

100

页码：

102699

DOI：

10.1016/j.parco.2020.102699

基金类别：

National Key Research and Development Program of China [2017YFB02018YFB1701400, 2018YFB0203804]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61873090, L1824034, L1924-056]; Ministry of Education China Mobile Research Fund Project [MCM20170506]; China Knowledge Centre for Engineering Sciences and Technology Project [CKCEST-2018-1-13, CKCE-ST-2019-2-13]

机构署名：

本校为其他机构

院系归属：

计算机科学与技术学院

摘要：

Spark Streaming is an extension of the core Spark engine that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. It treats stream as a series of deterministic batches and handles them as regular jobs. However, for a stream job responsible for a batch, data skew (i.e., the imbalance in the amount of data allocated to each reduce task), can degrade the job performance significantly because of load imbalance. In this paper, we propose an improved range partitioner (ImRP) to alleviate the reduce skew for stream jobs in Spark Streaming. Unlike previous work, I...

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ImRP: A Predictive Partition Method for Data Skew Alleviation in Spark Streaming Environment

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