Hadoop Developer Online Training

Hadoop Developer Online Training Course

Duration: 4-5 Weeks

Modulue-1

• An Introduction to Big Data
• THE EXPLOSION OF DATA
• Big Data Characteristics
• BI Vs Big Data
• Big Data Applications
• Big Data Framework
• Big Data Vender information

Module-2

• 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?

Module-3

• 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

Module-4

• 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

Module-5

• 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

Module-6

• An Introduction to Pig
• What is Pig?
• Pig’s Features
• Pig Use Cases
• Interacting with Pig
• Essential Points
• Conclusion

Module-7

• 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

Module-8

• 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

Module-9

• 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