摘要
语言虚拟机为大数据应用提供了与平台无关的执行环境,简化了应用的开发和部署,因此在大数据场景中得到了较广泛的应用。主要分析了两种主流语言虚拟机——JVM和CLR在大数据场景中的应用,并阐述了使用语言虚拟机面临的4个挑战:初始化及“热身”开销、垃圾回收暂停、异构内存支持、数据格式转换。之后,分别针对4个挑战讨论了现有的解决方案,并分析了这些方案的不足之处及未来可能的优化方向。
Language virtual machines provide a platform-independent execution environment for big-data applications and simplify their development and deployment phases,so they are widely used in the big-data scenario.The applications of two different kinds of mainstream language virtual machines:JVM and CLR,were analyzed,and four challenges when adopting language virtual machines:initialization and warm-up overhead,garbage collection pauses,heterogeneous memory support,and data layout transformation,were summarized.Afterward,existing approaches to the challenges were discussed and their shortcomings and possible optimizations in the future were analyzed.
作者
吴明瑜
陈海波
臧斌宇
WU Mingyu;CHEN Haibo;ZANG Binyu(Engineering Research Center for Domain-Specific Operating Systems,Ministry of Education,Shanghai 200240,China;Institute of Parallel and Distributed Systems,School of Software,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《大数据》
2020年第4期81-91,共11页
Big Data Research
基金
国家自然科学基金资助项目(No.61672345)。
关键词
语言虚拟机
垃圾回收
异构内存
language virtual machines
garbage collection
heterogeneous memory
