Hadoop / Big Data Training Syllabus

Hadoop / Bigdata Training Syllabus

Big Data Introduction

• What is Big Data
• Evolution of Big Data
• Benefits of Big Data
• Operational vs Analytical Big Data
• Need for Big Data Analytics
• Big Data Challenges

Hadoop cluster:

• Master Nodes
  • Name Node
  • Secondary Name Node
  • Job Tracker
• Client Nodes
• Slaves
• Hadoop configuration
• Setting up a Hadoop cluster

HDFS:

• Introduction to HDFS
• HDFS Features
• HDFS Architecture
• Blocks
• Goals of HDFS
• The Name node & Data Node
• Secondary Name node
• The Job Tracker
• The Process of a File Read
• How does a File Write work
• Data Replication
• Rack Awareness
• HDFS Federation
• Configuring HDFS
• HDFS Web Interface
• Fault tolerance
• Name node failure management
• Access HDFS from Java

Yarn

• Introduction to Yarn
• Why Yarn
• Classic MapReduce v/s Yarn
• Advantages of Yarn
• Yarn Architecture
  • Resource Manager
  • Node Manager
  • Application Master
• Application submission in YARN
• Node Manager containers
• Resource Manager components
• Yarn applications
• Scheduling in Yarn
  • Fair Scheduler
  • Capacity Scheduler
• Fault tolerance

MapReduce:

• What is MapReduce
• Why MapReduce
• How MapReduce works
• Difference between Hadoop 1 & Hadoop 2
• Identity mapper & reducer
• Data flow in MapReduce
• Input Splits
• Relation Between Input Splits and HDFS Blocks
• The flow of Job Submission in MapReduce
• Job submission & Monitoring
• MapReduce algorithms
  • Sorting
  • Searching
  • Indexing
  • TF-IDF

Hadoop Fundamentals:

• What is Hadoop
• History of Hadoop
• Hadoop Architecture
• Hadoop Ecosystem Components
• How does Hadoop work
• Why Hadoop & Big Data
• Hadoop Cluster introduction
• Cluster Modes
  • Standalone
  • Pseudo-distributed
  • Fully – distributed
• HDFS Overview
• Introduction to MapReduce
• Hadoop in demand

HDFS Operations:

• Starting HDFS
• Listing files in HDFS
• Writing a file into HDFS
• Reading data from HDFS
• Shutting down HDFS

HDFS Command Reference:

• Listing contents of the directory
• Displaying and printing disk usage
• Moving files & directories
• Copying files and directories
• Displaying file contents

Java Overview For Hadoop:

• Object-oriented concepts
• Variables and Data types
• Static data type
• Primitive data types
• Objects & Classes
• Java Operators
• Method and its types
• Constructors
• Conditional statements
• Looping in Java
• Access Modifiers
• Inheritance
• Polymorphism
• Method overloading & overriding
• Interfaces

MapReduce Programming:

• Hadoop data types
• The Mapper Class
  • Map method
• The Reducer Class
  • Shuffle Phase
  • Sort Phase
  • Secondary Sort
  •  Reduce Phase
• The Job class
  • Job class constructor
• JobContext interface
• Combiner Class
  • How Combiner works
  • Record Reader
  • Map Phase
  • Combiner Phase
  • Reducer Phase
  • Record Writer
• Partitioners
  • Input Data
  • Map Tasks
  • Partitioner Task
  • Reduce Task
  • Compilation & Execution

Hadoop Ecosystems

Pig:

• What is Apache Pig?
• Why Apache Pig?
• Pig features
• Where should Pig be used
• Where not to use Pig
• The Pig Architecture
• Pig components
• Pig v/s MapReduce
• Pig v/s SQL
• Pig v/s Hive
• Pig Installation
• Pig Execution Modes & Mechanisms
• Grunt Shell Commands
• Pig Latin – Data Model
• Pig Latin Statements
• Pig data types
• Pig Latin operators
• CaseSensitivity
• Grouping & Co Grouping in Pig Latin
• Sorting & Filtering
• Joins in Pig latin
• Built-in Function
• Writing UDFs
• Macros in Pig

HBase:

• What is HBase
• History Of HBase
• The NoSQL Scenario
• HBase & HDFS
• Physical Storage
• HBase v/s RDBMS
• Features of HBase
• HBase Data model
• Master server
• Region servers & Regions
• HBase Shell
• Create table and column family
• The HBase Client API

Spark:

• Introduction to Apache Spark
• Features of Spark
• Spark built on Hadoop
• Components of Spark
• Resilient Distributed Datasets
• Data Sharing using Spark RDD
• Iterative Operations on Spark RDD
• Interactive Operations on Spark RDD
• Spark shell
• RDD transformations
• Actions
• Programming with RDD
  • Start Shell
  • Create RDD
  • Execute Transformations
  • Caching Transformations
  • Applying Action
  • Checking output
• GraphX overview

Impala:

• Introducing Cloudera Impala
• Impala Benefits
• Features of Impala
• Relational databases vs Impala
• How Impala works
• Architecture of Impala
• Components of the Impala
  • The Impala Daemon
  • The Impala Statestore
  • The Impala Catalog Service
• Query Processing Interfaces
• Impala Shell Command Reference
• Impala Data Types
• Creating & deleting databases and tables
• Inserting & overwriting table data
• Record Fetching and ordering
• Grouping records
• Using the Union clause
• Working of Impala with Hive
• Impala v/s Hive v/s HBase

MongoDB Overview:

• Introduction to MongoDB
• MongoDB v/s RDBMS
• Why & Where to use MongoDB
• Databases & Collections
• Inserting & querying documents
• Schema Design
• CRUD Operations

Oozie & Hue Overview:

• Introduction to Apache Oozie
• Oozie Workflow
• Oozie Coordinators
• Property File
• Oozie Bundle system
• CLI and extensions
• Overview of Hue

Hive:

• What is Hive?
• Features of Hive
• The Hive Architecture
• Components of Hive
• Installation & configuration
• Primitive types
• Complex types
• Built in functions
• Hive UDFs
• Views & Indexes
• Hive Data Models
• Hive vs Pig
• Co-groups
• Importing data
• Hive DDL statements
• Hive Query Language
• Data types & Operators
• Type conversions
• Joins
• Sorting & controlling data flow
• local vs mapreduce mode
• Partitions
• Buckets

Sqoop:

• Introducing Sqoop
• Scoop installation
• Working of Sqoop
• Understanding connectors
• Importing data from MySQL to Hadoop HDFS
• Selective imports
• Importing data to Hive
• Importing to Hbase
• Exporting data to MySQL from Hadoop
• Controlling import process

Flume:

• What is Flume?
• Applications of Flume
• Advantages of Flume
• Flume architecture
• Data flow in Flume
• Flume features
• Flume Event
• Flume Agent
  •  Sources
  •  Channels
  •  Sinks
• Log Data in Flume

Zookeeper Overview:

• Zookeeper Introduction
• Distributed Application
• Benefits of Distributed Applications
• Why use Zookeeper
• Zookeeper Architecture
• Hierarchial Namespace
• Znodes
• Stat structure of a Znode
• Electing a leader

Kafka Basics:

• Messaging Systems
  • Point-to-Point
  • Publish – Subscribe
• What is Kafka
• Kafka Benefits
• Kafka Topics & Logs
• Partitions in Kafka
• Brokers
• Producers & Consumers
• What are Followers
• Kafka Cluster Architecture
• Kafka as a Pub-Sub Messaging
• Kafka as a Queue Messaging
• Role of Zookeeper
• Basic Kafka Operations
  • Creating a Kafka Topic
  • Listing out topics
  • Starting Producer
  • Starting Consumer
  • Modifying a Topic
  • Deleting a Topic
• Integration With Spark

Scala Basics:

• Introduction to Scala
• Spark & Scala interdependence
• Objects & Classes
• Class definition in Scala
• Creating Objects
• Scala Traits
• Basic Data Types
• Operators in Scala
• Control structures
• Fields in Scala
• Functions in Scala
• Collections in Scala
  • Mutable collection
  • Immutable collection

Project

Conclusion 

Went through our Hadoop / Big Data course Syllabus? Felt like an industrial-oriented Hadoop / Big Data Training Curriculum right? Then our Hadoop/ Big Data training in Chennai is your ideal destination. Enrol now.