Hadoop Development Online Training

Hadoop Development Online Training

Author: Subha Glory

                               Hadoop Development Online Training and Job Support Services is Offering by Glory IT Technologies With Real time Professionals. In this Course is Very Demand in the Market and Many number of Job Openings in the IT Companies. As all our faculty is more than 8+ years Experience and will cover all the topics. Hadoop Development Course Explain in Big data Motivation and Explaining all the components in Hadoop including, Hadoop Cluster and Distributed file systems and Hive and Pig Programmes. We provide regular and weekend classes as well as Normal or Fast track based on the Students Requirement  and Comfortable Timings. We Also provide Video classes as well for interested candidates.

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Module 1 – Introduction to Hadoop and its Ecosystem, Map Reduce and HDFS

  •  Big Data, Factors constituting Big Data
  •  Hadoop and Hadoop Ecosystem
  •  Map Reduce -Concepts of Map, Reduce, Ordering, Concurrency, Shuffle,
  • Reducing, Concurrency
  • Hadoop Distributed File System (HDFS) Concepts and its Importance
  •  Deep Dive in Map Reduce – Execution Framework, Partitioner, Combiner, Data
  • Types, Key pairs
  •  HDFS Deep Dive – Architecture, Data Replication, Name Node, Data Node, Data
  • Flow
  • Parallel Copying with DISTCP, Hadoop Archives 

Module 2 – Hands on Exercises

  • Installing Hadoop in Pseudo Distributed Mode, Understanding Important
  • configuration files, their Properties and Demon Threads
  •  Accessing HDFS from Command Line
  • Map Reduce – Basic Exercises
  •  Understanding Hadoop Eco-system
  •  Introduction to Sqoop, use cases and Installation
  • Introduction to Hive, use cases and Installation
  •  Introduction to Pig, use cases and Installation
  • Introduction to Oozie, use cases and Installation
  •  Introduction to Flume, use cases and Installation
  • Introduction to Yarn 

Module 3 – Deep Dive in Map Reduce and Yarn

  •  How to develop Map Reduce Application, writing unit test
  •  Best Practices for developing and writing, Debugging Map Reduce applications
  •  Joining Data sets in Map Reduce
  •  Hadoop API’s
  •  Introduction to Hadoop Yarn
  • Difference between Hadoop 1.0 and 2.0 

Module 3.1

  • Project 1- Hands on exercise – end to end PoC using Yarn or Hadoop 2.
1. Real World Transactions handling of Bank
2. Moving data using Sqoop to HDFS
3. Incremental update of data to HDFS
4. Running Map Reduce Program
5. Running Hive queries for data analytics
  •  Project 2- Hands on exercise – end to end PoC using Yarn or Hadoop 2.0 

Module 4 – Deep Dive in Pig

1. Introduction to Pig

  •  What Is Pig?
  • Pig’s Features
  • Pig Use Cases
  • Interacting with Pig

2. Basic Data Analysis with Pig

  •  Pig Latin Syntax
  •  Loading Data
  •  Simple Data Types
  •  Field Definitions
  •  Data Output
  •  Viewing the Schema
  •  Filtering and Sorting Data
  •  Commonly-Used Functions
  •  Hands-On Exercise: Using Pig for ETL Processing 

3. Processing Complex Data with Pig

  • Complex/Nested Data Types
  • Grouping
  • Iterating Grouped Data
  • Hands-On Exercise: Analyzing Data with Pig 

Module 5 – Deep Dive in Hive

1. Introduction to Hive
  •  What Is Hive?
  • Hive Schema and Data Storage
  • Comparing Hive to Traditional Databases
  • Hive vs. Pig
  • Hive Use Cases
  • Interacting with Hive
2. Relational Data Analysis with Hive
  •  Hive Databases and Tables
  • Basic HiveQL Syntax
  • Data Types
  • Joining Data Sets
  • Common Built-in Functions
  • Hands-On Exercise: Running Hive Queries on the Shell, Scripts, and Hue
3. Hive Data Management
  • Hive Data Formats
  • Creating Databases and Hive-Managed Tables
  • Loading Data into Hive
  • Altering Databases and Tables
  • Self-Managed Tables
  • Simplifying Queries with Views
  • Storing Query Results
  • Controlling Access to Data
  • Hands-On Exercise: Data Management with Hive
4. Hive Optimization
  • Understanding Query Performance
  • Partitioning
  • Bucketing
  • Indexing Data

Module 6 – Introduction to Hbase architecture

  • Introduction to HBase, Architecture, Map Reduce Integration, Different Client API
– Features and Administration. 

Module 7 – Hadoop Cluster Setup and Running Map Reduce Jobs

  • Hadoop Multi Node Cluster Setup using Amazon ec2 – Creating 4 node cluster
  • setup
  • Running Map Reduce Jobs on Cluster

Module 8 – Advance Mapreduce

  • Delving Deeper Into The Hadoop API
  • More Advanced Map Reduce Programming, Joining Data Sets in Map Reduce
  • Graph Manipulation in Hadoop