QEVIS:分布式查询执行的多粒度可视化
IEEE transactions on visualization and computer graphics
|October 26, 2023
概括
在像Apache Hive和Spark这样的系统中,QEVIS为分布式查询执行提供了增强的可视化. 它提供精细的,多视图的洞察力,以确定性能问题和执行异常.
科学领域:
- 计算机科学 计算机科学
- 数据工程数据工程
- 数据可视化 数据可视化
背景情况:
- 大规模的数据分析依赖于分布式查询处理系统 (例如Apache Hive,Spark).
- 了解查询执行对于性能优化和错误解决至关重要.
- 现有的可视化工具缺乏细致的任务级别细节和系统状态链接,阻碍了问题识别.
研究的目的:
- 介绍QEVIS,一个用于分布式查询执行的新型可视化系统.
- 通过提供细粒度,多视角分析来解决现有工具的局限性.
- 为了更容易地识别性能瓶和执行异常.
主要方法:
- 开发了一个查询逻辑计划布局算法,用于清晰的进展可视化.
- 提出了新的评分方法来量化和可视化工作和机器异常程度.
- 实现了基于散射图的任务视图,用于分析原子任务分布和交叉视图探索功能.
主要成果:
- 在原子任务和系统层面上,QEVIS可视化了分布式查询执行.
- 异常评分和任务分配模式有效地突出了绩效问题.
- 集成的辅助视图和交互可以有效地分析执行问题的根本原因.
结论:
- QEVIS克服了现有工具的局限性,提供了全面的多细分化可视化.
- 该系统帮助工程师诊断和解决分布式查询处理中的性能问题.
- 在生产环境中成功部署了QEVIS,证明了其实际有效性.
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