探索未锁定I/O驱动的单板计算机集群的效果和潜力
1Department of Convergence Security, Chung-Ang University, 84 Heukseok-ro, 06974, Dongjak-gu, Seoul, South Korea.
Scientific reports
|January 7, 2026
概括
单板电脑 (SBC) 集群,特别是带PCIe SSD的Raspberry Pi 5B,为千兆字节规模的大数据处理提供了一个实用的解决方案. 这项研究证明了它们对Hadoop集群的可行性,解决了成本和能源方面的问题.
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:
- 大数据处理依赖于Hadoop和Spark,推动对强大的服务器的需求,导致高成本和能源消耗.
- 单板计算机 (SBC) 集群是一个节能的替代方案,但存储I/O的限制阻碍了大数据处理.
- 在Raspberry Pi 5B中引入PCIe接口,使得高性能存储成为可能,克服了以前的SBC限制.
研究的目的:
- 调查SBC集群的可行性和潜力,用于千兆字节规模的大数据处理.
- 为了评估使用Raspberry Pi 5B SBC和基于PCIe的SSD构建的Hadoop集群的性能.
- 识别和讨论基于SBC的大数据处理的挑战和优化策略.
主要方法:
- 使用Raspberry Pi 5B (8GB RAM) 单板计算机构建了一个Hadoop集群.
- 集成的基于PCIe的高速固态驱动器 (SSD) 以提高存储性能.
- 通过使用高达2TB的数据集进行了六个已建立的大数据基准.
主要成果:
- 配有PCIe固态硬盘的Raspberry Pi 5B集群显示出了用于千兆字节规模大数据处理的巨大潜力.
- 性能受到包括I / O吞吐量,CPU超时,电源和SSD修饰命令在内的因素的影响.
- 优化的SBC配置可以实现实际的大数据处理能力.
结论:
- 带有PCIe支持的SSD的Raspberry Pi 5B SBC集群为大数据挑战提供了具有成本效益和能源效率的解决方案.
- 解决I/O瓶和优化系统参数对于最大化SBC集群性能至关重要.
- 这种方法为使用SBC集群进行实用,现实世界的大数据处理铺平了道路.
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