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相关概念视频

Maximum Size of Aggregate01:12

Maximum Size of Aggregate

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The maximum size of aggregate is defined as the aperture of the sieve retaining 15 percent or more of the particles present in the aggregate sample. The aggregate's maximum size impacts the concrete's water requirement, workability, and strength. Larger aggregates reduce the surface area needing cement paste coverage, which can lower water needs, thereby allowing a decrease in the water-to-cement ratio when the desired workability and richness of the mix are to be maintained, which can...
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Scaling01:26

Scaling

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In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...
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Statistical Analysis System (SAS)01:14

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SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
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Run charts serve as an essential instrument for visualizing the performance of various processes over time, enabling the identification of trends and patterns crucial for quality improvement. These charts map out a series of data points chronologically, offering insights into the stability and efficiency of a process. A run chart's creation involves plotting data points on a graph, with the time intervals on the horizontal axis and the specific measurements on the vertical axis. For...
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Statgraphics01:10

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Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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Updated: Dec 18, 2025

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DA:可扩展的无服务器数据分析和现场查询处理.

Elyes Lounissi1, Suvam Kumar Das2, Ronnit Peter2

  • 1National School of Computer Science (ENSI), University of Manouba, Manouba, Tunisia.

Journal of big data
|May 12, 2025
PubMed
概括
此摘要是机器生成的。

我们介绍Funda,一个无服务器的数据分析框架,用于本地环境. FunDa克服了当前无服务器解决方案的局限性,用于具有状态的,长时间运行的任务,如复杂的分析和SQL查询.

关键词:
这就是DaskDBDB.数据分析数据分析.在FUNDA FUNDA 里面.在现场查询处理.没有服务器的无服务器服务器

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科学领域:

  • 计算机科学 计算机科学
  • 云计算 云计算 云计算 云计算
  • 数据分析数据分析数据分析.

背景情况:

  • 无服务器云计算提供了支付-您-使用模式,有利于短暂的任务.
  • 现有的无服务器模式与状态,长期运行的数据分析和查询处理作斗争.

研究的目的:

  • 提出Funda,一个本地无服务器数据分析框架.
  • 为复杂的数据工作负载扩展无服务器计算的功能.
  • 在本地和公共云环境中实现无服务器操作.

主要方法:

  • 扩展DaskDB系统用于统一数据分析和现场SQL查询处理.
  • 为本地无服务器数据分析开发一个强大的架构.
  • 在本地和AWS云设置中对具有不同规模因子的基准进行系统评估.

主要成果:

  • FunDa展示了支持数据分析工作负载自动扩展的能力.
  • 该框架实现了复杂的数据分析任务的低延迟执行.
  • 实验结果显示,在本地和云环境中,无服务器用户的灵活性增加.

结论:

  • FunDa有效地解决了传统无服务器计算的局限性,用于状态,长期运行的数据分析.
  • 该框架为本地数据处理提供了一个可行的无服务器解决方案.
  • 在不同的环境中,FunDa提高了无服务器数据分析的灵活性和性能.