BIG DATA – HADOOP ADMIN COURSE IN JAIPUR

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What is BIG DATA – HADOOP ADMIN COURSE IN JAIPUR?

A Big Data – Hadoop Admin Course in Jaipur is a specialized training program designed to equip individuals with the skills required to manage and administer Hadoop clusters. Hadoop is a framework used for processing and storing large datasets in a distributed computing environment. This course is ideal for IT professionals who want to advance their careers in big data and Hadoop administration.

The Motivation & Limitation for Hadoop

  • Problems with Traditional Large-Scale Systems
  • Motivation & Limitation of Hadoop
  • Available version Hadoop 1.x & 2.x
  • Available Distributions of Hadoop (Cloudera, Hortonworks)
  • Hadoop Projects & Components
  • The Hadoop Distributed File System
    (HDFS)

Hadoop Ecosystem & Cluster
Hadoop Ecosystem projects &
Components overview

  • HDFS – File System
  • HBase – The Hadoop Database
  • Cassandra – No SOL Database
  • Hive – SQL Engine
  • Mahout

Hadoop Architecture overview Cluster
Daemons & Its Functions

  • Name Node
  • Secondary Node
  • Data Nodes

Planning Hadoop Cluster& Initial
Configuration

  • General Planning Considerations
  • Choosing the Right Hardware
  • Network Considerations
  • Planning for Cluster & Its Management
  • Types of Deployment
  • Cloudera Manager

Installation & Deployment of Hadoop

  • Installing Hadoop (Cloudera)
  • Installation – Pig, Hive, HBase, Cassandra etc
  • Specifying the Hadoop Configuration
  • Performing Initial HDFS
  • Configuration
  • Performing Initial YARN and
  • MapReduce Configuration
  • Hadoop Logging&Cluster Monitoring

Load Data and Run Application

  • Ingesting Data from External Sources withFlume
  • Ingesting Data from Relational
    Databaseswith Sqoop
  • REST Interfaces
  • Best Practices for Importing Data

Manage, Maintain, Monitor, and troubleshoot of cluster

  • General System Monitoring
  • Monitoring Hadoop Clusters
  • Common Troubleshooting Hadoop Clusters
  • Common Misconfigurations
  • Managing Running Jobs
  • Scheduling Hadoop Jobs

Upgrade, Rolling and Backup

  • Cluster Upgrading

  • Checking HDFS Status
  • Adding and Removing Cluster Nodes
  • Name Node Meta Data Backup
  • Data Backup
  • Distributed Copy
  • Parallel Data Ingestion

Conclusion & FAQs…

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