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Hadoop Scalable Distributed Computing


Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation.
  • Knowledge of Hadoop and Distributed Computing.
  • It is a 20 days program and extends up to 2hrs each.
  • The format is 40% theory, 60% Hands-on.

  • It is a 5 days program and extends up to 8hrs each.
  • The format is 40% theory, 60% Hands-on.
    Private Classroom arranged on request and minimum attendies for batch is 4.
course content
  • Getting Started with Hadoop Core
    • Understanding Data, Data Storage and Data Analysis
    • Introducing the MapReduce Model
    • Introducing Hadoop
    • Tracing the Hadoop History
    • Installing Hadoop
    • Running Hadoop Examples and Tests
    • Troubleshooting
  • Understanding MapReduce
    • An Example Dataset
    • Analyzing the Data with Unix Tools
    • Analyzing the Data with Hadoop
    • Scaling Out
    • Hadoop Streaming
    • Hadoop Pipes
  • Understanding the Hadoop Distributed Filesystem
    • The Design of HDFS
    • HDFS Concepts
    • The Command-Line Interface
    • Hadoop Filesystems
    • The Java Interface
    • Data Flow
    • Parallel Copying with distcp
    • Hadoop Archives
  • Working with Hadoop I/O
    • Data Integrity
    • Compression
    • Serialization
    • File-Based Data Structures
  • Developing a MapReduce Application
    • The Configuration API
    • Configuring the Development Environment
    • Writing a Unit Test
    • Running Locally on Test Data
    • Running on a Cluster
    • Tuning a Job
    • MapReduce Workflows
  • Explaining How MapReduce Works
    • Anatomy of a MapReduce Job Run
    • Failures
    • Job Scheduling
    • Shuffle and Sort
    • Task Execution
  • Discussing MapReduce Types and Formats
    • MapReduce Types
    • Input Formats
    • Output Formats
  • Explaining MapReduce Features
    • Counters
    • Sorting
    • Joins
    • Side Data Distribution
    • MapReduce Library Classes
  • Setting Up a Hadoop Cluster
    • Cluster Specification
    • Cluster Setup and Installation
    • SSH Configuration
    • Hadoop Configuration
    • Post Install
    • Benchmarking a Hadoop Cluster
    • Hadoop in the Cloud
  • Administering Hadoop
    • HDFS
    • Monitoring
    • Maintenance
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