{"title":"BAShuffler: Maximizing Network Bandwidth Utilization in the Shuffle of YARN","authors":"Feng Liang, F. Lau","doi":"10.1145/2907294.2907296","DOIUrl":null,"url":null,"abstract":"YARN is a popular cluster resource management platform. It does not, however, manage the network bandwidth resources which can significantly affect the execution performance of those tasks having large volumes of data to transfer within the cluster. The shuffle phase of MapReduce jobs features many such tasks. The impact of under utilization of the network bandwidth in shuffle tasks is more pronounced if the network bandwidth capacities of the nodes in the cluster are varied. We present BAShuffler, a bandwidth-aware shuffle scheduler, that can maximize the overall network bandwidth utilization by scheduling the source nodes of the fetch flows at the application level. BAShuffler can fully utilize the network bandwidth capacity in a max-min fair network. The experimental results for a variety of realistic benchmarks show that BAShuffler can substantially improve the cluster's shuffle throughput and reduce the execution time of shuffle tasks as compared to the original YARN, especially in heterogeneous network bandwidth environments.","PeriodicalId":20515,"journal":{"name":"Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2016-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2907294.2907296","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
YARN is a popular cluster resource management platform. It does not, however, manage the network bandwidth resources which can significantly affect the execution performance of those tasks having large volumes of data to transfer within the cluster. The shuffle phase of MapReduce jobs features many such tasks. The impact of under utilization of the network bandwidth in shuffle tasks is more pronounced if the network bandwidth capacities of the nodes in the cluster are varied. We present BAShuffler, a bandwidth-aware shuffle scheduler, that can maximize the overall network bandwidth utilization by scheduling the source nodes of the fetch flows at the application level. BAShuffler can fully utilize the network bandwidth capacity in a max-min fair network. The experimental results for a variety of realistic benchmarks show that BAShuffler can substantially improve the cluster's shuffle throughput and reduce the execution time of shuffle tasks as compared to the original YARN, especially in heterogeneous network bandwidth environments.