HADOOP Online Training

Hadoop is especially well-suited to large data processing tasks (like searching and indexing) because it can leverage its distributed file system to cheaply and reliably replicate chunks of data to nodes in the cluster, making data available locally on the machine that is processing it.Hadoop is written in Java. Hadoop programs can be written using a small API in Java or Python. Hadoop is a rapidly evolving ecosystem of components for implementing the Google MapReduce algorithms in a scalable fashion on commodity hardware.

Hadoop can also run binaries and shell scripts on nodes in the cluster provided that they conform to a particular convention for string input/output. As with many other types of information technology (IT) solutions, change management and systems monitoring are a primary consideration within Hadoop.

HADOOP Online Training Course Content
  • Introduction to Big Data and Hadoop
    • What is Hadoop?
    • History of Hadoop
    • Building Blocks – Hadoop Eco-System
    • Who is behind Hadoop?
    • What Hadoop is good for and why it is Good
  • HDFS
    • Configuring HDFS
    • Interacting With HDFS
    • HDFS Permissions and Security
    • Additional HDFS Tasks
    • HDFS Overview and Architecture
    • HDFS Installation
    • Hadoop File System Shell
    • File System Java API
  • MAPREDUCE
    • Map/Reduce Overview and Architecture
    • Installation
    • Developing Map/Red Jobs
    • Input and Output Formats
    • Job Configuration
    • Job Submission
  • Getting Started With Eclipse IDE
    • Configuring Hadoop API on Eclipse IDE
    • Connecting Eclipse IDE to HDFS
  • Hadoop Streaming
  • Advanced MapReduce Features
    • Custom Data Types
    • Input Formats
    • Output Formats
    • Partitioning Data
    • Reporting Custom Metrics
    • Distributing Auxiliary Job Data
  • Distributing Debug Scripts
  • Using Yahoo Web Services
  • Pig
    • Pig Overview
    • Installation
    • Pig Latin
    • Pig with HDFS
  • Hive
    • Hive Overview
    • Installation
    • Hive QL
    • Hive Unstructured Data Analyzation
    • Hive Semistructured Data Analyzation
  • HBase
    • HBase Overview and Architecture
    • HBase Installation
    • HBase Shell
    • CRUD operations
    • Scanning and Batching
    • Filters
    • HBase Key Design
  • ZooKeeper
    • Zoo Keeper Overview
    • Installation
    • Server Mantainace
  • Sqoop
    • Sqoop Overview
    • Installation
    • Imports and Exports
  • CONFIGURATION
    • Basic Setup
    • Important Directories
    • Selecting Machines
    • Cluster Configurations
    • Small Clusters: 2-10 Nodes
    • Medium Clusters: 10-40 Nodes
    • Large Clusters: Multiple Racks
  • Integrations

Please Register with us