HADOOP Online Training Course Content

Duration: 5-6 Weeks

  •     An Introduction to Big Data
  •     The explosion of Data
  •     Big Data Characteristics
  •     BI Vs Big Data
  •     Big Data Applications
  •     Big Data Framework
  •     Big Data Vendor information
  •     Big Data Approaches
  •     Approaches to Process Big Data (Phases)
  •     Traditional Database analytics
  •     Massive Parallel Processing
  •     Cloud Computing
  •     Grid Computing
  •     Map Reduce
  •     What problems exist with ‘traditional’ large-scale computing Systems?
  •     What requirements an alternative approach should have?
  •     How Hadoop addresses those requirements?
  •     The Hadoop Basic concepts
  •     What Hadoop is
  •     What features the Hadoop Distributed File System (HDFS) provides
  •     The concepts behind MapReduce
  •     How a Hadoop cluster operates
  •     What other Hadoop Ecosystem projects exist
  •     Introduction to Map Reduce
  •     MapReduce Architecture
  •     Fault tolerance in MapReduce
  •     Sample applications
  •     Getting started with Hadoop
  •     Higher-level languages on top of Hadoop: Pig and Hive
  •     Integrating Hadoop Into The Workflow
  •     Introduction
  •     Relational Database Management Systems
  •     Storage Systems
  •     Importing Data From RDBMSs With Sqoop
  •     Hands-On Exercise
  •     Importing Real-Time Data With Flume
  •     Accessing HDFS Using FuseDFS and Hoop
  •     Conclusion
  •     An Introduction to Pig
  •     What is Pig?
  •     Pig’s Features
  •     Pig Use Cases
  •     Interacting with Pig
  •     Essential Points
  •     Conclusion
  •     Basic Data Analysis with Pig
  •     Basic Syntax of Pig Latin
  •     How to load and store data using Pig
  •     Which datatypes Pig uses to represent data
  •     How to sort and filter data in Pig
  •     How to use many of Pig’s built in functions for data processing
  •     Processing Complex Data with Pig
  •     How Pig uses bags,tuples,and maps to represent complex data.
  •     The Techniques Pig provides to for grouping and ungrouping data.
  •     How to use aggregate functions in Pig Latin
  •     How to iterate through records in complex data structures.
  •     Multi Dataset Operations with Pig
  •     How we can use grouping to combine data from multiple sources.
  •     What types of join operators Pig supports and how to use them.
  •     How to concatenate records to produce a single data set.
  •     How to split a single data set into multiple relations
  •     Introduction to Hive
  •     What is Hive
  •     How Hive differs from a relational database.
  •     Ways in which organizations use Hive.
  •     How to invoke and interact with Hive.
  •     Relational Data with Hive
  •     How to explore database and tables in Hive.
  •     How HiveQL syntax compared with SQL
  •     Which datatypes Hive supports.
  •     Join operators in Hive
  •     Built in functions in Hive.
  •     Hive Data Management
  •     How Hive encodes and stores data
  •     How to create Hive databases,tables and views.
  •     How to load data into tables
  •     How to alter and remove tables
  •     How to save query results into tables and files.
  •     How to control access to data in Hive
  •     Important String Functions
  •     What is HBase?
  •     When To Use HBase?
  •     HBase Data Model
  •     HBase Logical View
  •     HBase Physical Model
  •     Major Components Of HBase
  •     HBase Big Picture
  •     Compaction
  •     HBase Shell
  •     HBase Useful Commands
  •     Hand’s On exercise
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