Distributed Data Platform System Based on Hadoop Platform

2014 ◽  
pp. 533-539 ◽  
Author(s):  
Jianwei Guo ◽  
Liping Du ◽  
Ying Li ◽  
Guifen Zhao ◽  
Jiang Jiya
Keyword(s):  
Distributed Data ◽  
Data Platform ◽  
Hadoop Platform ◽  
Platform System

scholarly journals Design and Implementation of Real-time Power Grid WebGIS Visualization Framework Based on New Generation Dispatching and Control System

2021 ◽  
Vol 2087 (1) ◽  
pp. 012073
Author(s):  
Yuan He ◽  
Yuan Zhang ◽  
Yaowei Zhang ◽  
Caishen Fang ◽  
Kun Huang ◽  
...  
Keyword(s):  
Control System ◽  
Real Time ◽  
Power Grid ◽  
Secondary Development ◽  
Control Data ◽  
Cartographic Generalization ◽  
Data Platform ◽  
Platform System ◽  
New Generation ◽  
And Control

Abstract With the strengthening of the integrated characteristics of power grid and the construction of the New Generation Dispatching and Control System with “physical distribution, logical integration”, the demand for global monitoring and analysis of power grid has gradually increased. On the basis of understanding of design of the new generation real-time dispatching and control data platform system, with the principles of componentization and servitization, the real-time power grid WebGIS visualization framework is designed and implemented. And this paper further introduces the design of the front-end secondary development interface and examples, as well as the cartographic generalization of the power grid WebGIS visual map. This framework has successfully supported the construction and online operation of several real-time power grid WebGIS visualization applications.

Distributed Data Platform for Machine Learning Using the Fog Computing Model

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Takeshi Tsuchiya ◽  
Ryuichi Mochizuki ◽  
Hiroo Hirose ◽  
Tetsuyasu Yamada ◽  
Keiichi Koyanagi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Fog Computing ◽  
Distributed Data ◽  
Computing Model ◽  
Data Platform

Treatment and Research of Massive Data Mining Based on Cloud Computing

2013 ◽  
Vol 765-767 ◽  
pp. 941-944
Author(s):  
Peng Wang ◽  
Jia Nan Wang ◽  
Ji Ci Ba ◽  
Yu Tan
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Data Processing ◽  
Programming Model ◽  
Massive Data ◽  
Distributed Data ◽  
Distributed Data Processing ◽  
Hadoop Platform ◽  
Core Framework

This paper introduces SPRINT algorithm optimized in the Hadoop core framework. Combing the data mining process, we will study the cloud computing in the MapReduce programming model, then improve and optimize the SPRINT algorithm in conjunction with the mode, transplant the optimized algorithm to Hadoop platform for distributed data processing.

scholarly journals Text Mining with Apache Hadoop Over different Hadoop Clusters Architectures

2019 ◽  
Vol 8 (2) ◽  
pp. 1252-1256
Keyword(s):  
Big Data ◽  
Text Mining ◽  
Real Time ◽  
Single Node ◽  
Text Documents ◽  
Apache Hadoop ◽  
Data Platform ◽  
Hadoop Distributed File System ◽  
Hadoop Platform ◽  
Hadoop Clusters

Big data is very much practical for real time applicational systems. One of the mostly used real time application worldwide are on unstructured documents. Large number of documents are managed and maintained through popular leadingBig Data platform is Hadoop. It maintains all the information at Hadoop Distributed File System in Blocks. Irrespective of datasize, BigData has opened its path to store and analyze the data which has consumed time. To overcome this, Hadoophas designed cluster process for large volumes of unstructured data computations. Three different cluster architectures like Standalone, Single node cluster and multi node clusters are considered. In this paper, Big Data allows Hadoop platform to boost the processing speed overlarge datasets through cluster architectures, which are studied and analyzed through text documents from newsgroup20 dataset.It identifies the challenges on text mining and its applications using ApacheHadoop

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