Jie Zhang, Zhiyuan Li, Yidou You, R. Huang, Jin Liu, Xu Chen
{"title":"Optimization of Merge Policy in AsterixDB Big Data Management System","authors":"Jie Zhang, Zhiyuan Li, Yidou You, R. Huang, Jin Liu, Xu Chen","doi":"10.1109/IIKI.2016.29","DOIUrl":null,"url":null,"abstract":"AsterixDB Big Data Management System isone of the non-relational databases, developed and researched by researcher in UC Irvine, UC Riverside, andUC San Diego. One of the basic storage structures of AsterixDB is a log structured merge tree, and the log structured merge tree cannot get away from merging operations. When we research in this project closely, we foundthat a better merge policy helps improve the CURD performance of log structured merge tree in a great level. The existing merging policies show a lot of drawbackswhen data size gets bigger and bigger. Our method aimsat optimizing merge policy utilizing a new scheduler–Level Scheduler which was proposed in [6]. Experimentsshow that our merge algorithm is much more efficient.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIKI.2016.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
AsterixDB Big Data Management System isone of the non-relational databases, developed and researched by researcher in UC Irvine, UC Riverside, andUC San Diego. One of the basic storage structures of AsterixDB is a log structured merge tree, and the log structured merge tree cannot get away from merging operations. When we research in this project closely, we foundthat a better merge policy helps improve the CURD performance of log structured merge tree in a great level. The existing merging policies show a lot of drawbackswhen data size gets bigger and bigger. Our method aimsat optimizing merge policy utilizing a new scheduler–Level Scheduler which was proposed in [6]. Experimentsshow that our merge algorithm is much more efficient.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
