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PRAGIM Technologies: HADOOP Course Contents
  • OOP and Java
  • Object Oriented Concepts
  • Language Fundamentals
  • Inheritance
  • Polymorphism
  • Interface
  • Collections
  • Exceptions
  • Multi Threadings
  • Introduction to Big Data
  • What is Big Data
  • Distributed Systems and Hadoop
  • SQL verses Hadoop
  • History of Hadoop
  • Map Reduce Paper by Google
  • Apache Hadoop
  • Cloudera Hadoop
  • Hadoop Components
  • Hadoop Eco-System
  • Hadoop Use Cases
  • HDFS
  • Building blocks of HDFS
  • Key design principles
  • Deployment Models
  • Configuring and Starting hadoop services
  • HDFS Tools
  • HDFS Web Page
  • working with HDFS
  • HDFS Lab Assignment
  • Map Reduce
  • Understanding Map Reduce
  • Job Tracker Web Page
  • Hadoop Maintenance Activities
  • Running Hadoop in Cluster
  • Map Reduce APIs
  • Data Types, Input and output formats
  • Improving performance with Combiner
  • Partitioner
  • Counters
  • Setup and Teardown
  • Side Data Distribution
  • Lazy Output Creation
  • No Reducers
  • Tuning for performance by Speculative execution
  • Map Reduce Lab Assignment
  • Advanced Map Reduce Concepts
  • Multiple Inputs
  • Job Chaining
  • Small Files Problem
  • Compression
  • Hadoop Streaming
  • Map and Reduce Side Joins
  • Sqoop
  • What is Sqoop?
  • Install & configure sqoop
  • Sqoop Import
  • Sqoop Export
  • Sqoop Lab Assignment
  • Hive
  • What is Hive
  • Hive Architecture
  • Configuring Hive
  • Hive Data Models and Types
  • working with Hive Queries
  • Hive Programming assignment
  • Pig
  • Think like a Pig
  • Pig Latin
  • Pig Architecture
  • Installing and running
  • Data Types
  • Common Query Algorithms
  • User Defined Functions (UDF)
  • Use Cases
  • Pig Programming Assignment
  • Best Practices
  • Using Combiner
  • Using Compression
  • Hadoop Hardware planning
  • Hadoop in cloud
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