Best way to learn hadoop - PowerPoint PPT Presentation

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Best way to learn hadoop

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Keep yourself upgraded with the latest software techniques running in the market by getting trained with the real time faculty of Sun Trainings who can drive you through most latest & upgraded software skills. Attend our free demo session online and get direct connect with our trainers. We offer trainings in USA, UK, Ausralia and Canada also. Kindly register your query on contact@suntrainings.com / (M) 9642434362 . – PowerPoint PPT presentation

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Title: Best way to learn hadoop


1
Big Data Hadoop
  • Bigdata Hadoop Course Description
  • sun trainings is a best hadoop online training
    institute in hyderabad . We are providing good
    online training on Hadoop.
  • Course Name Bigdata Hadoop facultyReal time
    Experience
  •  
    MAIL ID
    contact_at_suntrainings.com

  • PH NO
    91 9642434362

2
  • Course Objective Summary
  • Introduction to Big Data and Hadoop
  • Hadoop ecosystem - Concepts
  • Hadoop Map-reduce concepts and features
  • Developing the map-reduce Applications
  • Pig concepts
  • Hive concepts
  • Oozie workflow concepts
  • Flume Concepts
  • Hue Concepts
  • HBASE Concepts
  • Real Life Use Cases
  • Virtual box/VM Ware
  • Basics
  • Installations
  • Backups
  • Snapshots

3
  • Linux
  • Basics
  • Installations
  • Commands
  • Hadoop
  • Why Hadoop?
  • Scaling
  • Distributed Framework
  • Hadoop v/s RDBMS
  • Brief history of hadoop
  • Setup hadoop
  • Pseudo mode
  • Cluster mode
  • Ipv6
  • Ssh
  • Installation of java, hadoop
  • Configurations of hadoop
  • Hadoop Processes ( NN, SNN, JT, DN, TT)
  • Temporary directory

4
  • HDFS- Hadoop distributed File System
  • HDFS Design and Architecture
  • HDFS Concepts
  • Interacting HDFS using command line
  • Interacting HDFS using Java APIs
  • Dataflow
  • Blocks
  • Replica
  • Hadoop Processes
  • Name node
  • Secondary name node
  • Job tracker
  • Task tracker
  • Data node
  • Map Reduce
  • Developing Map Reduce Application
  • Phases in Map Reduce Framework
  • Map Reduce Input and Output Formats
  • Advanced Concepts

5
  • Joining datasets in Mapreduce jobs
  • Map-side join
  • Reduce-Side join
  • Map reduce customization
  • Custom Input format class
  • Hash Partitioner
  • Custom Partitioner
  • Sorting techniques
  • Custom Output format class
  • Hadoop Programming Languages -
  • I).HIVE
  • Introduction
  • Installation and Configuration
  • Interacting HDFS using HIVE
  • Map Reduce Programs through HIVE
  • HIVE Commands
  • Loading, Filtering, Grouping.
  • Data types, Operators..
  • Joins, Groups.
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