Overview Hadoop Development

IT Trainings

  • OVERVIEW HADOOP DEVELOPER
  • 11. Introduction

  • 12. The Motivation for Hadoop
  • • Problems with traditional large-scale systems
  • • Requirements for a new approach

  • 13. Hadoop: Basic Concepts
  • • An Overview of Hadoop
  • • The Hadoop Distributed File System
  • • Hands-On Exercise
  • • How MapReduce Works
  • • Hands-On Exercise
  • • Anatomy of a Hadoop Cluster
  • • Other Hadoop Ecosystem Components

  • 14. Writing a MapReduce Program
  • • The MapReduce Flow
  • • Examining a Sample MapReduce Program
  • • Basic MapReduce API Concepts
  • • The Driver Code
  • • The Mapper
  • • The Reducer
  • • Hadoop’s Streaming API
  • • Using Eclipse for Rapid Development
  • • Hands-on exercise
  • • The New MapReduce API

  • 15. Common MapReduce Algorithms
  • • Sorting and Searching
  • • Indexing
  • • Machine Learning With Mahout
  • • Term Frequency – Inverse Document Frequency
  • • Word Co-Occurrence
  • • Hands-On Exercise.

  • 16.PIG Concepts..
  • • Data loading in PIG.
  • • Data Extraction in PIG.
  • • Data Transformation in PIG.
  • • Hands on exercise on PIG.

  • 17. Hive Concepts.
  • • Hive Query Language.
  • • Alter and Delete in Hive.
  • • Partition in Hive.
  • • Indexing.
  • • Joins in Hive.Unions in hive.
  • • Industry specific configuration of hive parameters.
  • • Authentication & Authorization.
  • • Statistics with Hive.
  • • Archiving in Hive.
  • • Hands-on exercise

  • 18. Working with Sqoop
  • • Introduction.
  • • Import Data.
  • • Export Data.
  • • Sqoop Syntaxs.
  • • Databases connection.
  • • Hands-on exercise

  • 19. Working with Flume
  • • Introduction.
  • • Configuration and Setup.
  • • Flume Sink with example.
  • • Channel.
  • • Flume Source with example.
  • • Complex flume architecture.

  • 20. OOZIE Concepts
  • 21. IMPALA Concepts
  • 22. HUE Concepts
  • 23. HBASE Concepts
  • 24. ZooKeeper concepts