一个基于Hadoop的分布式数据处理方案,用于同步辐射实验
Ding Zhang1, Ze Yi Dai1, Xue Ping Sun1
1The Institute for Advanced Studies, Wuhan University, Wuhan 430072, People's Republic of China.
Journal of synchrotron radiation
|April 24, 2024
概括
同步辐射实验产生大数据,需要并行处理. 本研究介绍了一种基于Hadoop的大数据框架,用于高效,可扩展的同步仪数据分析.
科学领域:
- 材料科学 材料科学 材料科学
- 物理 物理学 物理
- 数据科学数据科学数据科学
背景情况:
- 同步射线辐射源和高率探测器在实验数据中产生指数级增长.
- 数据的快速增长需要在同步辐射束线上的并行处理能力.
- 现有的数据处理解决方案缺乏与大数据技术框架的整合.
研究的目的:
- 介绍一套新的分布式数据处理方案,用于同步辐射光束线实验数据.
- 利用Apache Hadoop大数据框架来有效地存储和计算大规模的科学数据集.
- 开发一个可扩展和可靠的数据处理平台,以适应现代同步机实验的需求.
主要方法:
- 使用Hadoop分布式文件系统 (HDFS) 进行分布式文件存储.
- 雇佣了Hadoop Yet Another资源谈判器 (YARN) 作为分布式计算集群的资源调度器.
- 设计和开发了一个使用Hadoop Spark进行大规模并行计算的分布式数据处理管道.
主要成果:
- 成功实施了用于同步辐射光束线数据的分布式数据处理平台.
- 该平台通过并行计算证明了对大规模数据集的高效处理.
- 微服务架构确保了系统可扩展性,减少了模块合,并提高了可靠性.
结论:
- 开发的基于Hadoop的框架为同步辐射实验中的大数据处理提供了关键的解决方案.
- 这种方法使得光线线能够有效地管理和分析指数级增长的实验数据.
- 可扩展和可靠的平台通过高效的数据处理来支持科学发现的进步.
相关概念视频
Cluster Sampling Method
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Radiation: Applications
The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
The average...
The average...
Distributed Loads
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
Distributed Loads: Problem Solving
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
Parallel Processing
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...


