1. Big Data
1.1. Big Data Definition
1.2. Big Data Types
1.3. Big Data Source
1.4. Big Data Challenges
1.5. Big Data Benefits
1.6. Big Data Applications
1.7. Netflix Application

2. Apache Hadoop
2.1. Introduction
2.2. Advantages & Disadvantages
2.3. History of Hadoop Project
2.4. Need for Hadoop
2.5. Hadoop Architecture
2.6. RDBMS vs Hadoop
2.7. Vendor Comparison
2.8. Hardware Recommendations
2.9. Hadoop Installation

3. HDFS
3.1. Basics (Blocks, Namenodes and Datanodes)
3.2. HDFS Architecture
3.3. Data Read and Write Process
3.4. HDFS Permissions
3.5. Data Replication
3.6. HDFS Accessibility
3.7. HDFS Filesystem Operations
3.8. HDFS Interfaces
3.9. Heartbeats
3.10. Rack Awareness
3.11. distcp

4. MapReduce
4.1. MapReduce Basics
4.2. MapReduce Work Flow
4.3. MapReduce Framework
4.4. Hadoop Data Types
4.5. MapReduce Internals
4.6. Job Formats
4.7. Debugging and Profiling
4.8. Distributed Cache
4.9. Combiner Functions
4.10. Streaming
4.11. Counters, Sorting and Joins

5. YARN
5.1. YARN Infrastructure
5.2. ResourceManager
5.3. ApplicationMaster
5.4. NodeManager
5.5. Container

6. Pig
6.1. Pig Architecture
6.2. Installation and Modes
6.3. Grunt and Pig Script
6.4. Pig Latin Commands
6.5. UDF and Data Processing Operator

7. HBase
7.1. HBase Architecture
7.2. HBase Installation
7.3. HBase Configuration
7.4. HBase Schema Design
7.5. HBase Commands
7.6. MapReduce Integration
7.7. HBase Security

8. Sqoop and Flume
8.1. Sqoop
8.2. Flume

9. Hive
9.1. Hive Architecture
9.2. Hive shell
9.3. Hive Data types
9.4. HiveQL

10. Workflow
10.1. Apache Oozie

11. Hadoop Cluster Management
11.1. Cluster Planning
11.2. Installation and Configuration
11.3. Testing
11.4. Benchmarking
11.5. Monitoring

12. Administration
12.1. dfsadmin, fsck and balancer
12.2. Logging
12.3. Data Backup
12.4. Add and removal of nodes

13. Security
13.1. Authentication
13.2. Data Confidentiality
13.3. Configuration

14. NextGen Hadoop
14.1. HDFS HA
14.2. HDFS Federation

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