在私有云上集成可扩展的分析工具和数据仓库
Kazumasa Kishimoto1,2, Osamu Sugiyama3, Tomohide Iwao1,2
1Kyoto University, Kyoto, Japan.
Studies in health technology and informatics
|August 8, 2025
概括
本研究介绍了一个可扩展的数据仓库解决方案,集成了本地和私有云环境. 它使用Kubernetes进行安全的虚拟机,实现快速数据提取和安全的云API访问,以满足各种分析需求.
科学领域:
- 计算机科学 计算机科学
- 数据工程数据工程
- 云计算 云计算 云计算
背景情况:
- 对高效,可扩展的数据仓储解决方案的需求日益增加.
- 安全地与私有云基础设施集成本地数据的挑战.
- 需要动态和安全的数据分析环境.
研究的目的:
- 开发和评估一个高效和可扩展的数据仓库解决方案.
- 将本地环境与私有云基础设施集成.
- 为数据分析提供安全,独立的虚拟环境.
主要方法:
- 利用Kubernetes来动态生成安全的虚拟机.
- 实现了医院网络和谷歌云之间的VPN连接,以实现安全的API访问.
- 对数据提取和查询速度进行了性能测试.
主要成果:
- 实现了快速查询速度,在12.4秒内从301GB的数据集中提取了24万条记录.
- 证明了与谷歌云端的内部数据的安全集成.
- 验证了基础设施的可扩展性,以满足各种分析要求.
结论:
- 开发的解决方案为数据仓储提供了一种高效且可扩展的方法.
- 库伯内特和安全的云连接使强大的数据分析环境成为可能.
- 该基础设施支持各种分析需求,同时保持数据安全.
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