Cost of Fault-Tolerance on Data Stream Processing

被引:0
|
作者
Vianello, Valerio [1 ]
Patino-Martinez, Marta [1 ]
Azqueta-Alzuar, Ainhoa [1 ]
Jimenez-Peris, Ricardo [2 ]
机构
[1] Univ Politecn Madrid, Madrid, Spain
[2] LeanXcale, Madrid, Spain
来源
EURO-PAR 2018: PARALLEL PROCESSING WORKSHOPS | 2019年 / 11339卷
基金
欧盟地平线“2020”;
关键词
Data streaming; Fault tolerance; Evaluation; HiBench;
D O I
10.1007/978-3-030-10549-5_2
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Data streaming engines process data on the fly in contrast to databases that first, store the data and then, they process it. In order to process the increasing amount of data produced every day, data streaming engines run on top of a distributed system. In this setting failures will likely happen. Current distributed data streaming engines like Apache Flink provide fault tolerance. In this paper we evaluate the impact on performance of fault tolerance mechanisms of Flink during regular operation (when there are no failures) on a distributed system and the impact on performance when there are failures. We use the Intel HiBench for conducting the evaluation.
引用
收藏
页码:17 / 27
页数:11
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