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Course Outlines

Hadoop Course Curriculum

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    Duration: One month

    Part 1 (Introducing Big Data)

  • Understand Big Data
  • Limits of traditional systems
  • Big Data vs. EDW
  • Big Data vs. Cloud
  • Big Data vs. HPC
  • Why Hadoop (Introduction)
  • Brief history
  • Concepts of distributed file system
  • Hadoop eco system
  • Hadoop alternatives
  • Scenarios
  • Part 2 (Hadoop In-depth)

  • Hadoop distributed file system (HDFS)
  • Hadoop core daemons
  • Hadoop Map Reduce Framework
  • Hand shake of core components
  • Job scheduling logic
  • In-depth into Mappers, Reducers, sorting and shuffling
  • File read and write semantics
  • Bulk operations
  • Hands-on & Assignments
  • Part 3 (Detailing Hadoop Eco system)

  • Apache Hive
  • Hive Hands-on
  • Apache Pig
  • Pig Hands-on
  • Apache HBase
  • HBase hands-on
  • Apache Scoop
  • Scoop hands-on
  • Apache Flume
  • Apache Hue
  • Apache Mahout
  • Apache Oozie
  • Apache Ambari
  • Hands-on & Assignments
  • Part 4 (Hadoop Integrations, real world scenarios)

  • Hive with Pig
  • Hive with HBase
  • Pig with HBase
  • Scoop with Hive
  • Scoop with HBase
  • Python integration
  • Hands-on & Assignments
  • Part 5 (Hadoop 2.0)

  • Challenges in Hadoop 1.x
  • Name node high availability
  • HDFS Federation
  • Resource Manager – YARN
  • Node Manager
  • App Master
  • Hands-on & Assignments
  • Part 6 (Hadoop Administration)

  • Refresh on Unix/Linux commands
  • Planning for Hadoop cluster
  • Hardware and Software considerations
  • Setting up a standalone system
  • Setting up a pseudo distributed system
  • Hadoop daemon addresses and ports
  • Managing Jobs
  • Types of Schedulers in Hadoop
  • Configuring scheduler and run a job
  • Cluster monitoring and trouble shooting

Course Info

Learn Hadoop

Big Data or Hadoop online training is very suitable for professionals to learn the concepts of Hadoop, Apache Hadoop Software operations and managing complex data sets.

Hadoop is a Java based programmer which supports the processing of huge data in computing environment. It is a fragment of Apache venture that is supported by Apache software Foundation.

Hadoop online training makes the learners possibility to run application with thousands of nodes connecting thousands of terabytes on systems. It is a distributed file system enables quick data transfer duties among the nodes and allows the systems to remain operating continuous in the instance of a node interruption. This tactic reduces the risk of catastrophic system failure, even if many nodes don’t function.

Big Classes introduce the learners by Hadoop training with Hadoop working methodology. Where Hadoop is an inspiration of Google’s MapReduce, software framework where an application is fragmented into several small parts. These fragments run on any node of a cluster. The recent Apache Hadoop ecosystem consists of Hadoop distributed file system (HDFS),MapReduce, Hadoop kernel and a number of associated projects such as HBase, Zookeeper and Apache Hive.

Hadoop Framework is often used by big companies like Google, IBM and Yahoo largely by the applications those are involved in search engines and advertising organizations.

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