Online Big Data Hadoop Training in USA,UK,Canada,Australia,Dubai,Hyderabad,Bangalore,Mumbai - PowerPoint PPT Presentation

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Online Big Data Hadoop Training in USA,UK,Canada,Australia,Dubai,Hyderabad,Bangalore,Mumbai

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Title: Online Big Data Hadoop Training in USA,UK,Canada,Australia,Dubai,Hyderabad,Bangalore,Mumbai


1
A1Trainings
  • Online Big Data Hadoop Training in
    USA,UK,Canada,Australia,Dubai,Hyderabad,Bangalore,
    Mumbai

2
Hadoop Course Content
3
During this course, you will learn
  • 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

4
Virtual box/VM Ware
  • Basics
  • Installations
  • Backups
  • Snapshots

5
Linux
  • Basics
  • Installations
  • Commands

6
Hadoop
  • Why Hadoop?
  • Scaling
  • Distributed Framework
  • Hadoop v/s RDBMS
  • Brief history of hadoop

7
Setup hadoop
  • Pseudo mode
  • Cluster mode
  • Ipv6
  • Ssh
  • Installation of java, hadoop
  • Configurations of hadoop
  • Hadoop Processes ( NN, SNN, JT, DN, TT)
  • Temporary directory
  • UI
  • Common errors when running hadoop cluster,
    solutions

8
HDFS- Hadoop distributed File System
  • HDFS Design and Architecture
  • HDFS Concepts
  • Interacting HDFS using command line
  • Interacting HDFS using Java APIs
  • Dataflow
  • Blocks
  • Replica

9
Hadoop Processes
  • Name node
  • Secondary name node
  • Job tracker
  • Task tracker
  • Data node

10
Map Reduce
  • Developing Map Reduce Application
  • Phases in Map Reduce Framework
  • Map Reduce Input and Output Formats
  • Advanced Concepts
  • Sample Applications
  • Combiner

11
Joining datasets in Mapreduce jobs
  • Map-side join
  • Reduce-Side join

12
Map reduce customization
  • Custom Input format class
  • Hash Partitioner
  • Custom Partitioner
  • Sorting techniques
  • Custom Output format class

13
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.
  • Sample programs in HIVE

14
II).PIG
  • Basics
  • Installation and Configurations
  • Commands.
  • OVERVIEW HADOOP DEVELOPER

15
IntroductionThe Motivation for Hadoop
  • Problems with traditional large-scale systems
  • Requirements for a new approach

16
Hadoop Basic Concepts
  • Map-side join
  • Reduce-Side join

17
Introduction
  • 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

18
Writing a MapReduce Program
  • The MapReduce Flow
  • Examining a Sample MapReduce Program
  • Basic MapReduce API Concepts
  • The Driver Code
  • The Mapper
  • The Reducer
  • Hadoops Streaming API
  • Using Eclipse for Rapid Development
  • Hands-on exercise
  • The New MapReduce API

19
Common MapReduce Algorithms
  • Sorting and Searching
  • Indexing
  • Machine Learning With Mahout
  • Term Frequency Inverse Document Frequency
  • Word Co-Occurrence
  • Hands-On Exercise.

20
PIG Concepts..
  • Data loading in PIG.
  • Data Extraction in PIG.
  • Data Transformation in PIG.
  • Hands on exercise on PIG.

21
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

22
Working with Sqoop
  • Introduction.
  • Import Data.
  • Export Data.
  • Sqoop Syntaxs.
  • Databases connection.
  • Hands-on exercise

23
Working with Flume--------------02 Hours
  • Introduction.
  • Configuration and Setup.
  • Flume Sink with example.
  • Channel.
  • Flume Source with example.
  • Complex flume architecture.
  • OOZIE Concepts
  • IMPALA Concepts
  • HUE Concepts

24
Reporting Tool
  • Tableau Software
  • 1.Tableau Fundamentals.
  • 2.Tableau Analytics.
  • 3.Visual Analytics.
  • 4. Hands-on exercise

25
About Us
  • Contact Info
  • Address Madhapur, Hyderabad.
  • Email contact_at_a1trainings.com
  • Call us 7680813158
  • Web www.a1trainings.com
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