ArcaDB:用于异质计算环境的分类查询引擎
Kristalys Ruiz-Rohena1, Manuel Rodriguez-Martínez2
1Department of Electrical and Computer Engineering, University of Puerto Rico, Mayagüez.
概括
ArcaDB是一个新的数据分析引擎,使用容器技术来优化查询性能. 它智能地将数据处理任务放在合适的硬件上,比传统系统快3.5倍的结果.
科学领域:
- 计算机科学 计算机科学
- 数据工程数据工程
- 高性能计算 高性能计算
背景情况:
- 现代企业需要对大型数据集进行强大的数据管理.
- 像GPU和TPU这样的硬件加速器对于扩展数据处理至关重要.
- 现有的数据分析引擎需要架构演变,以利用新的硬件趋势.
研究的目的:
- 介绍ArcaDB,一个针对现代数据分析而设计的分类查询引擎.
- 展示ArcaDB如何利用容器技术来实现高效的操作员配置.
- 评估ArcaDB提供的性能改进.
主要方法:
- 开发了ArcaDB,这是一个使用Java,Python和Docker容器的分类查询引擎.
- 实施了一个系统,在该系统中,查询计划被发送到具有不同计算特性的工节点.
- 有注释的运算符与首选的计算节点类型,以优化执行.
主要成果:
- ArcaDB成功地将运营商放置在匹配其性能配置的计算节点上.
- 创建了一个原型实现,并使用图像和科学数据进行了测试.
- 初步研究表明,与共享无任何架构相比,ArcaDB可将查询性能提高3.5倍.
结论:
- ArcaDB的分类架构和基于容器的操作员配置提高了数据分析的效率.
- 该引擎有效地利用异质计算节点来提高查询性能.
- 对于现代硬件,ArcaDB代表了数据分析引擎设计的重大进步.
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