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Implementation of a distributed processing engine for spatial big-data processing based on batch and stream

机译:基于批量和流的空间大数据处理的分布式处理引擎的实现

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摘要

Recently, the amount of spatial information generated in real time due to the use of SNS is increasing rapidly. Research is also actively underway to extract only the information of interest from real-time spatial information. Then, the spatial information generated in the SNS can be requested by the API of the corresponding SNS company. In this case, the responding spatial information is provided to the requester in the form of stream in JSON format, and a dedicated ETL tool capable of processing the spatial information of the stream type is needed. In order to continuously process the massive spatial information of the stream type, the distributed and parallel processing method should be used rather than the existing single processing method. At this time, the necessary ETL tools are distributed and parallel ETL tools. In this paper, we design and implement a spatial ETL processing engine that can process spatial information on a stream basis as well as an ETL processing spatial information on the existing layout base. The spatial ETL processing engine proposed in this paper is a spatial ETL engine for distributed processing. For the general user, the unit module experiment was commissioned by TTA(Telecommunication Technology Association).
机译:最近,由于使用SNS而实时产生的空间信息的量正在迅速增加。研究也积极正在进行中提取利用实时空间信息的兴趣信息。然后,可以由SNS中生成的空间信息由相应的SNS公司的API请求。在这种情况下,响应空间信息以JSON格式以流的形式提供给请求者,并且需要能够处理流类型的空间信息的专用ETL工具。为了不断处理流类型的大量空间信息,应使用分布式和并行处理方法而不是现有的单个处理方法。此时,“必要的ETL工具”是分布式和并行ETL工具。在本文中,我们设计并实现了一种空间ETL处理引擎,其可以在流的基础上处理空间信息以及关于现有布局基础的ETL处理空间信息。本文提出的空间ETL处理引擎是用于分布处理的空间ETL发动机。对于普通用户,单位模块实验由TTA(电信技术协会)委托。

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