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Big Data and Hadoop Course Curriculum

Module 1: Introduction to Big Data
Introduction to Big Data and Hadoop
Big Data Analytics
What is Big Data?
Four v’s of Big Data
Rise of Big Data
Compare Hadoop vs traditional systems
Hadoop Master-Slave Architecture
Understanding HDFS Architecture
NameNode, DataNode, Secondary Node
Learn about JobTracker, TaskTracker, Resource Manager, Node Manager

Module 2: HDFS and MapReduce Architecture
Hadoop Architecture Distributed Storage (HDFS) and Yarn
What is HDFS
Need for HDFS
Regular File System vs HDFS
Characteristics of HDFS
HDFS Architecture and Components
High Availability Cluster Implementations
HDFS Component File System Namespace
Data Block Split
Data Replication Topology
HDFS Command Line
Yarn Introduction
Yarn Use Case
Yarn and Its Architecture
Resource Manager
How Resource Manager Operates
Application Master
How Yarn Runs an Application
Tools for Yarn Developers
Core components of Hadoop
Understanding Hadoop Master-Slave Architecture
Learn about NameNode, DataNode, Secondary Node
Understanding HDFS Architecture
Anatomy of Read and Write data on HDFS
MapReduce Architecture Flow
JobTracker and TaskTracker
Resource Manager and Node Manager

Module 3:  Hadoop Configuration
Hadoop Modes
Hadoop Terminal Commands
Cluster Configuration
Web Ports
Hadoop Configuration Files
Reporting, Recovery
MapReduce in Action

Module 4: Understanding Hadoop MapReduce Framework
Overview of the MapReduce Framework
Use cases of MapReduce
MapReduce Architecture
Anatomy of MapReduce Program
Mapper/Reducer Class, Driver code
Understand Combiner and Partitioner

Module 5: Advance MapReduce – Part 1
Write your own Partitioner
Writing Map and Reduce in Python
Map side/Reduce side Join
Distributed Join
Distributed Cache
Counters
Joining Multiple datasets in MapReduce
Module 6: Advance MapReduce – Part 2
MapReduce internals
Understanding Input Format
Custom Input Format
Using Writable and Comparable
Understanding Output Format
Sequence Files
JUnit and MRUnit Testing Frameworks

Module 7: Apache Pig
Apache Pig Introduction
Apache Pig Architecture
Apache Pig Installation
Apache Pig Execution
Apache Pig Grunt Shell
Apache Pig – Reading Data
Apache Pig – Storing Data
Apache Pig – Diagnostic Operator
Apache Pig – Describe Operator
Apache Pig – Explain Operator
Apache Pig – Illustrate Operator
Apache Pig – Group Operator
Apache Pig – Cogroup Operator
Apache Pig – Join Operator
Apache Pig – Cross Operator
Apache Pig – Union Operator
Apache Pig – Split Operator
Apache Pig – Filter Operator
Apache Pig – Distinct Operator
Apache Pig – Foreach Operator
Apache Pig – Order By
Apache Pig – Limit Operator
Apache Pig – Eval Functions
Apache Pig – Bag & Tuple Functions
Apache Pig – String Functions
Apache Pig – date-time Functions
Apache Pig – Math Functions

Module 8: Apache Hive and HiveQL
Hive – Introduction
Hive – Installation
Hive – Data Types
Hive – Create Database
Hive – Drop Database
Hive – Create Table
Hive – Alter Table
Hive – Drop Table
Hive – Partitioning
Hive – Built-In Operators
Hive – Built-In Functions
Hive – Views And Indexes
Difference between Hive and RDBMS

Module 9: Advance HiveQL
Multi-Table Inserts
Joins
Grouping Sets, Cubes, Rollups
Custom Map and Reduce scripts
Hive SerDe
Hive UDF
Hive UDAF
Hive Partitioning
Dynamic Partitioning in Hive
Hive Bucketing
Hive Partitioning and Bucketing together
Hive Data Sampling

Module 10: Apache Flume, Sqoop, Oozie
Sqoop – How Sqoop works
Sqoop Architecture
Flume – How it works
Flume Complex Flow – Multiplexing
Oozie – Simple/Complex Flow
Oozie Service/ Scheduler
Use Cases – Time and Data triggers

Module 11 NoSQL Databases
CAP theorem
RDBMS vs NoSQL
Key Value stores: Memcached, Riak
Key Value stores: Redis, Dynamo DB
Column Family: Cassandra, HBase
Graph Store: Neo4J
Document Store: MongoDB, CouchDB

Module 12 Apache HBase
When/Why to use HBase
HBase Architecture/Storage
HBase Data Model
HBase Families/ Column Families
HBase Master
HBase vs RDBMS
Access HBase Data
HBase – Overview
HBase – Architecture
HBase – Installation
HBase – Shell
HBase – General Commands
HBase – Admin API
HBase – Create Table
HBase – Listing Table
HBase – Disabling a Table
HBase – Enabling a Table
HBase – Describe & Alter
HBase – Exists
HBase – Drop a Table
HBase – Shutting Down
HBase – Client API
HBase – Create Data
HBase – Update Data
HBase – Read Data
HBase – Delete Data
HBase – Scan
HBase – Count & Truncate
HBase – Security

Module 13 Apache Zookeeper
What is Zookeeper
Zookeeper Data Model
ZNokde Types
Sequential ZNodes
Installing and Configuring
Running Zookeeper
Zookeeper use cases

Module 14 Hadoop 2.0, YARN, MRv2
Hadoop 1.0 Limitations
MapReduce Limitations
HDFS 2: Architecture
HDFS 2: High availability
HDFS 2: Federation
YARN Architecture
Classic vs YARN
YARN multitenancy
YARN Capacity Scheduler
Module 15: Basics of Functional Programming and Scala
Scala – Overview
Scala – Environment Setup
Scala – Basic Syntax
Scala – Data Types
Scala – Variables
Scala – Classes & Objects
Scala – Access Modifiers
Scala – Operators
Scala – IF ELSE
Scala – Loop Statements
Scala – Functions
Scala – Closures
Scala – Strings
Scala – Arrays
Scala – Collections
Scala – Traits
Scala – Pattern Matching
Scala – Regular Expressions
Scala – Exception Handling
Scala – Extractors
Scala – Files I/O
Module 16: Apache Spark Next-Generation Big Data Framework
History of Spark
Limitations of Mapreduce in Hadoop
Introduction to Apache Spark
Components of Spark
Application of In-memory Processing
Hadoop Ecosystem vs Spark
Advantages of Spark
Spark Architecture
Spark Cluster in Real World
Demo: Running a Scala Programs in Spark Shell
Demo: Setting Up Execution Environment in Ide
Demo: Spark Web UI
Apache Spark – Core Programming
Apache Spark – Deployment
Advanced Spark Programming
Module 17: Spark MLLib Modelling BigData with Spark
Spark Mllib Modeling Big Data With Spark
Role of Data Scientist and Data Analyst in Big Data
Analytics in Spark
Machine Learning
Supervised Learning
Demo: Classification of Linear Svm
Demo: Linear Regression With Real World Case Studies
Unsupervised Learning
Demo: Unsupervised Clustering K-means
Reinforcement Learning
Semi-supervised Learning
Overview of Mllib