東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Using Big Data Tools to Analyze Geog...

Jain, Divya.

Linked to FindBook

Google Book

Amazon

博客來

Using Big Data Tools to Analyze Geographical Related Data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using Big Data Tools to Analyze Geographical Related Data./
Author:	Jain, Divya.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	55 p.
Notes:	Source: Masters Abstracts International, Volume: 56-05.
Contained By:	Masters Abstracts International56-05(E).
Subject:	Computer science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10623649
ISBN:	9780355228533

Using Big Data Tools to Analyze Geographical Related Data.
Jain, Divya.

Using Big Data Tools to Analyze Geographical Related Data. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 55 p.

Source: Masters Abstracts International, Volume: 56-05.

Thesis (M.S.)--San Diego State University, 2017.

Big data has revolutionized the techniques used in data analysis as large enterprises have huge datasets that keep growing every day. These datasets require large storage capacity and management and can be structured, semi structured or unstructured. They also need different software frameworks, which differ from conventional databases such as the Hadoop framework which make data management easier in this era of large-scale data. Hadoop Distributed File System (HDFS) is critical in managing data that has been stored in cloud systems.

ISBN: 9780355228533Subjects--Topical Terms:

523869
Computer science.

Using Big Data Tools to Analyze Geographical Related Data.
LDR:02083nmm a2200313 4500 001 2202239
005 20190513114645.5
008 201008s2017 ||||||||||||||||| ||eng d
020 $a 9780355228533
035 $a (MiAaPQ)AAI10623649
035 $a (MiAaPQ)sdsu:11732
035 $a AAI10623649
040 $a MiAaPQ $c MiAaPQ
100 1 $a Jain, Divya. $3 3346606
245 1 0 $a Using Big Data Tools to Analyze Geographical Related Data.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 55 p.
500 $a Source: Masters Abstracts International, Volume: 56-05.
500 $a Adviser: Carl Eckberg.
502 $a Thesis (M.S.)--San Diego State University, 2017.
520 $a Big data has revolutionized the techniques used in data analysis as large enterprises have huge datasets that keep growing every day. These datasets require large storage capacity and management and can be structured, semi structured or unstructured. They also need different software frameworks, which differ from conventional databases such as the Hadoop framework which make data management easier in this era of large-scale data. Hadoop Distributed File System (HDFS) is critical in managing data that has been stored in cloud systems.
520 $a Hadoop has ability to solve the problem of handling and processing a huge amount of data in various formats as traditional RDBMS (Relational Database Management System) approach is inefficient and time consuming for processing of large data sets.
520 $a This thesis explores using the Hadoop Ecosystem to analyze a particular data set, based on images. The data was obtained from a large collection of machine learning data sets at UC Irvine. To apply this sample exploration to actual large data, one can automate obtaining properties of images, and then go to picture sharing sites like Flickr, and explore truly big data in various ways.
590 $a School code: 0220.
650 4 $a Computer science. $3 523869
690 $a 0984
710 2 $a San Diego State University. $b Computer Science. $3 2102764
773 0 $t Masters Abstracts International $g 56-05(E).
790 $a 0220
791 $a M.S.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10623649