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
- 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
- An Introduction to Pig
- What is Pig?
- Pig’s Features
- Pig Use Cases
- Interacting with Pig
- Essential Points
- 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
- HBase Shell
- HBase Useful Commands
- Hand’s On exercise