1.1 Big Data Introduction

1.2 Distributed systems

1.3 Big Data Use Cases

1.4 Various Solutions

1.5 Overview of Hadoop Ecosystem

1.6 Spark Ecosystem Walkthrough

1.7 Quiz

2.1 Understanding the CloudxLab

2.2 Getting Started - Hands on

2.3 Hadoop & Spark Hands-on

2.4 Quiz and Assessment

2.5 Basics of Linux - Quick Hands-On

2.6 Understanding Regular Expressions

2.7 Quiz and Assessment

2.8 Setting up VM (optional)

3.1 ZooKeeper - Race Condition

3.2 ZooKeeper - Deadlock

3.3 Hands-On

3.4 Quiz & Assessment

3.5 How does election happen - Paxos Algorithm?

3.6 Use cases

3.7 When not to use

3.8 Quiz & Assessment

4.1 Why HDFS or Why not existing file systems?

4.2 HDFS - NameNode & DataNodes

4.3 Quiz

4.4 Advance HDFS Concepts (HA, Federation)

4.5 Quiz

4.6 Hands-on with HDFS (Upload, Download, SetRep)

4.7 Quiz & Assessment

4.8 Data Locality (Rack Awareness)

5.1 YARN - Why not existing tools?

5.2 YARN - Evolution from MapReduce 1.0

5.3 Resource Management: YARN Architecture

5.4 Advance Concepts - Speculative Execution

5.5 Quiz

6.1 MapReduce - Understanding Sorting6.2 MapReduce - Overview

6.3 Quiz

6.4 Example 0 - Word Frequency Problem - Without MR

6.5 Example 1 - Only Mapper - Image Resizing

6.6 Example 2 - Word Frequency Problem

6.7 Example 3 - Temperature Problem

6.8 Example 4 - Multiple Reducer

6.9 Example 5 - Java MapReduce Walkthrough

6.10 Quiz

7.1 Writing MapReduce Code Using Java

7.2 Building MapReduce project using Apache Ant

7.3 Concept - Associative & Commutative

7.4 Quiz

7.5 Example 8 - Combiner

7.6 Example 9 - Hadoop Streaming

7.7 Example 10 - Adv. Problem Solving - Anagrams

7.8 Example 11 - Adv. Problem Solving - Same DNA

7.9 Example 12 - Adv. Problem Solving - Similar DNA

7.10 Example 12 - Joins - Voting

7.11 Limitations of MapReduce

7.12 Quiz

8.1 Pig - Introduction

8.2 Pig - Modes

8.3 Getting Started

8.4 Example - NYSE Stock Exchange

8.5 Concept - Lazy Evaluation

9.1 Hive - Introduction

9.2 Hive - Data Types

9.3 Getting Started

9.4 Loading Data in Hive (Tables)

9.5 Example: Movielens Data Processing

9.6 Advance Concepts: Views

9.7 Connecting Tableau and HiveServer 2

9.8 Connecting Microsoft Excel and HiveServer 2

9.9 Project: Sentiment Analyses of Twitter Data

9.10 Advanced - Partition Tables

9.11 Understanding HCatalog & Impala

9.12 Quiz

10.1 NoSQL - Scaling Out / Up

10.2 NoSQL - ACID Properties and RDBMS Story

10.3 CAP Theorem

10.4 HBase Architecture - Region Servers etc

10.5 Hbase Data Model - Column Family Orientedness

10.6 Getting Started - Create table, Adding Data

10.7 Adv Example - Google Links Storage

10.8 Concept - Bloom Filter

10.9 Comparison of NOSQL Databases

10.10 Quiz

11.1 Sqoop - Introduction

11.2 Sqoop Import - MySQL to HDFS

11.3 Exporting to MySQL from HDFS

11.4 Concept - Unbounding Dataset Processing or Stream Processing

11.5 Flume Overview: Agents - Source, Sink, Channel

11.6 Example 1 - Data from Local network service into HDFS

11.7 Example 2 - Extracting Twitter Data

11.8 Quiz

11.9 Example 3 - Creating workflow with Oozie

1.1 Apache Spark ecosystem walkthrough

1.2 Spark Introduction - Why Spark?

1.3 Quiz

2.1 Scala - Quick Introduction - Access Scala on CloudxLab2.2 Scala - Quick Introduction - Variables and Methods

2.3 Getting Started: Interactive, Compilation, SBT

2.4 Types, Variables & Values

2.5 Functions

2.6 Collections

2.7 Classes

2.8 Parameters

2.9 More Features

2.10 Quiz and Assessment

3.1 Apache Spark ecosystem walkthrough3.2 Spark Introduction - Why Spark?

3.3 Using the Spark Shell on CloudxLab

3.4 Example 1 - Performing Word Count

3.5 Understanding Spark Cluster Modes on YARN

3.6 RDDs (Resilient Distributed Datasets)

3.7 General RDD Operations: Transformations & Actions

3.8 RDD lineage

3.9 RDD Persistence Overview

3.10 Distributed Persistence

4.1 Creating the SparkContext

4.2 Building a Spark Application (Scala, Java, Python)

4.3 The Spark Application Web UI

4.4 Configuring Spark Properties

4.5 Running Spark on Cluster

4.6 RDD Partitions

4.7 Executing Parallel Operations

4.8 Stages and Tasks

5.1 Common Spark Use Cases

5.2 Example 1 - Data Cleaning (Movielens)

5.3 Example 2 - Understanding Spark Streaming

5.4 Understanding Kafka

5.5 Example 3 - Spark Streaming from Kafka

5.6 Iterative Algorithms in Spark

5.7 Project: Real-time analytics of orders in an e-commerce company

6.1 InputFormat and InputSplit

6.2 JSON

6.3 XML

6.4 AVRO

6.5 How to store many small files - SequenceFile?

6.6 Parquet

6.7 Protocol Buffers

6.8 Comparing Compressions

6.9 Understanding Row Oriented and Column Oriented Formats - RCFile?

7.1 Spark SQL - Introduction

7.2 Spark SQL - Dataframe Introduction

7.3 Transforming and Querying DataFrames

7.4 Saving DataFrames

7.5 DataFrames and RDDs

7.6 Comparing Spark SQL, Impala, and Hive-on-Spark

8.1 Machine Learning Introduction

8.2 Applications Of Machine Learning

8.3 MlLib Example: k-means

8.4 SparkR Example