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Introduction to Hadoop
  1. The amount of data processing in today’s life
  2. What Hadoop is why it is important?
  3. Hadoop comparison with traditional systems
  4. Hadoop history
  5. Hadoop main components and architecture
Hadoop Distributed File System (HDFS)
  1. HDFS overview and design
  2. HDFS architecture
  3. HDFS file storage
  4. Component failures and recoveries
  5. Block placement
  6. Balancing the Hadoop cluster
Planning your Hadoop cluster
  1. Planning a Hadoop cluster and its capacity
  2. Hadoop software and hardware configuration
  3. HDFS Block replication and rack awareness
  4. Network topology for Hadoop cluster
Hadoop Deployment
  1. Different Hadoop deployment types
  2. Hadoop distribution options
  3. Hadoop competitors
  4. Hadoop installation procedure
  5. Distributed cluster architecture
  6. Lab: Hadoop Installation
Working with HDFS
  1. Ways of accessing data in HDFS
  2. Common HDFS operations and commands
  3. Different HDFS commands
  4. Internals of a file read in HDFS
  5. Data copying with ‘distcp’
  6. Lab: Working with HDFS
Map-Reduce Abstraction
  1. What MapReduce is and why it is popular
  2. The Big Picture of the MapReduce
  3. MapReduce process and terminology
  4. MapReduce components failures and recoveries
  5. Working with MapReduce
Hadoop Cluster Configuration
  1. Hadoop configuration overview and important configuration file
  2. Configuration parameters and values
  3. HDFS parameters MapReduce parameters
  4. Hadoop environment setup
  5. ‘Include’ and ‘Exclude’ configuration files
  6. Lab: MapReduce Performance Tuning
Hadoop Administration and Maintenance
  1. Namenode/Datanode directory structures and files
  2. File system image and Edit log
  3. The Checkpoint Procedure
  4. Namenode failure and recovery procedure
  5. Safe Mode
  6. Metadata and Data backup
  7. Potential problems and solutions / what to look for
  8. Adding and removing nodes
  9. Lab: MapReduce File system Recovery
Hadoop Monitoring and Troubleshooting
  1. Best practices of monitoring a Hadoop cluster
  2. Using logs and stack traces for monitoring and troubleshooting
  3. Using open-source tools to monitor Hadoop cluster
Job Scheduling
  1. How to schedule Hadoop Jobs on the same cluster
  2. Default Hadoop FIFO Schedule
  3. Fair Scheduler and its configuration
Hadoop Multi Node Cluster Setup and Running Map Reduce Jobs on Amazon Ec2
  1. Hadoop Multi Node Cluster Setup using Amazon ec2 – Creating 4 node cluster setup
  2. Running Map Reduce Jobs on Cluster
High Availability Fedration, Yarn and Security