Hadoop Developer Online Training

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Hadoop Developer Online Training Course

Duration: 4-5 Weeks

  • An Introduction to Big Data
  • Big Data Characteristics
  • BI Vs Big Data
  • Big Data Applications
  • Big Data Framework
  • Big Data Vender 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