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Month: February 2018
This article explains the setup of the Hadoop Multi-Node cluster on a distributed environment. As the whole cluster cannot be demonstrated, we are explaining the Hadoop cluster environment using three systems (one master and two slaves); given below are their IP addresses. Hadoop Master: 192.168.1.15 (hadoop-master) Hadoop Slave: 192.168.1.16 (hadoop-slave-1) Hadoop Slave: 192.168.1.17 (hadoop-slave-2) Follow … Continue reading Hadoop – Multi Node Cluster
Introduction HDFS is an Apache Software Foundation project and a subproject of the Apache Hadoop project. Hadoop is ideal for storing large amounts of data, like terabytes and petabytes, and uses HDFS as its storage system. HDFS lets you connect nodes (commodity personal computers) contained within clusters over which data files are distributed. You can … Continue reading An introduction to the Hadoop Distributed File System
Starting HDFS Format the configured HDFS file system and then open the namenode (HDFS server) and execute the following command. $ hadoop namenode -format Start the distributed file system and follow the command listed below to start the namenode as well as the data nodes in cluster. $ start-dfs.sh Listing Files in HDFS Finding the … Continue reading HDFS Operations
Introduction to Hadoop Distributed File System Hadoop File System was mainly developed for using distributed file system design. It is highly fault tolerant and holds huge amount of data sets and provides ease of access. The files are stored across multiple machines in a systematic order. These stored files are stored to eliminate all possible … Continue reading HDFS Overview
Hadoop is supported by Linux platform and its facilities. So install a Linux OS for setting up Hadoop environment. If you own an operating system than Linux then you can install virtual machine and have Linux inside the virtual machine. Prerequisites Hadoop is written in Java programming, so there exists the necessity of Java installed … Continue reading Hadoop Installation
Apache Hadoop was born to enhance the usage and solve major issues of big data. The web media was generating loads of information on a daily basis, and it was becoming very difficult to manage the data of around one billion pages of content. In order of revolutionary, Google invented a new methodology of processing … Continue reading Introduction to Hadoop
Big data is a term defined for data sets that are large or complex that traditional data processing applications are inadequate. Big Data basically consists of analysis zing, capturing the data, data creation, searching, sharing, storage capacity, transfer, visualization, and querying and information privacy. What is Big Data? Big Data is a collection of large … Continue reading Big Data Overview
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