Processing of Medical Different Types of Data Using Hadoop and Java']Java MapReduce

被引：0

作者：

Boyko, Nataliya ^{[1
]}

Tkachuk, Nazar ^{[1
]}

机构：

[1] Lviv Polytech Natl Univ, Profesorska St 1, UA-79013 Lvov, Ukraine

来源：

IDDM 2020: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON INFORMATICS & DATA-DRIVEN MEDICINE | 2020年 / 2753卷

关键词：

Data processing; Hadoop; !text type='Java']Java[!/text] Map/Reduce; Heterogeneous data processing; MapReduce; Big data; Data Analysis; HDFS; multiple input;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article shows the analysis of sample data of different types using Java MapReduce on the Hadoop platform. The Java programming language and the Java MapReduce API are used to work on large amounts of data ("Big Data") that have different formats and structures. So, the task was to process the medical data and get a single source file. The result of the program was saved in the HDFS file system. These source data can then be saved to the NTFS file system using Sqoop or the files can be copied manually to the system for further processing.

引用

页数：9

共 19 条

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