Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/2316| Title: | Study of Distributed File System for Big Data |
| Authors: | Zalte, Sagar A. Takate, Vishwas R. Chaudhari, Saish R. |
| Keywords: | Hadoop HDFS distributed file system Map-Reduce |
| Issue Date: | 1-Feb-2017 |
| Abstract: | The caption for Hadoop is big data analytics. That means perform Analytics over big data. Traditional technologies such as R, SQL, and Vertica cannot deal with big data. Hadoop can store unstructured semi structured and structured data. Two core component of Hadoop are 1.HDFS 2.Map Reduce. The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications. Map Reduce is an execution engine of Hadoop, it process the data stored in HDFS in distributed manner. |
| URI: | http://192.168.3.232:8080/jspui/handle/123456789/2316 |
| Appears in Collections: | Study of Distributed File System for Big Data |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.