Hadoop Administration Online Training Course Content


Understanding Big Data and Hadoop


Learning Objectives: In this module, you will understand what is Big Data and Apache Hadoop. You will also learn how Hadoop solves the Big Data problems, Hadoop Cluster Architecture, its core components & ecosystem, Hadoop data loading & reading mechanism and role of a Hadoop Cluster Administrator.

  • Introduction to big data
  • limitations of existing solutions
  • Hadoop architecture
  • Hadoop components and ecosystem
  • data loading & reading from HDFS
  • replication rules
  • rack awareness theory
  • Hadoop cluster administrator: Roles and responsibilities

Hadoop Architecture and Cluster setup


Learning Objectives: In this module, you will understand different Hadoop components; understand the working of HDFS, Hadoop cluster modes, configuration files, and more. You will also understand the Hadoop 2.0 cluster setup and configuration, setting up Hadoop Clients using Hadoop 2.0 and resolve problems simulated from a real-time environment.

  • Hadoop server roles and their usage
  • Hadoop installation and initial configuration
  • Deploying Hadoop in a pseudo-distributed mode
  • Deploying a multi-node Hadoop cluster
  • Installing Hadoop Clients
  • Understanding the working of HDFS and resolving simulated problems

Hadoop Cluster Administration and Understanding MapReduce


Learning Objectives: In this module you will understand the working of the secondary namenode, working with Hadoop distributed cluster, enabling rack awareness, maintenance mode of Hadoop cluster, adding or removing nodes to your cluster in an ad-hoc and recommended way, understand the MapReduce programming model in the context of Hadoop administrator and schedules.

  • Understanding secondary namenode
  • Working with Hadoop distributed cluster
  • Decommissioning or commissioning of nodes
  • Understanding MapReduce
  • Understanding schedulers and enabling them

Backup, Recovery and Maintenance


Learning Objectives: In this module, you will understand the day to day cluster administration tasks, balancing data in a cluster, protecting data by enabling trash, attempting a manual failover, creating backup within or across clusters, safeguarding your metadata and doing metadata recovery or manual failover of NameNode recovery, learn how to restrict the usage of HDFS in terms of count and volume of data, and more.

  • Key Hadoop Admin Commands
  • Trash
  • Import Check Point
  • Distcp, data backup, and recovery
  • Enabling trash
  • Namespace count quota or space quota
  • Manual failover or metadata recovery

Cluster planning and management


Learning Objectives: In this module, you will gather insights around cluster planning and management; learn about the various aspects one needs to remember while planning a setup of a new cluster, capacity sizing, understanding recommendations and comparing different distributions of Hadoop, understanding workload and usage patterns and some examples from the world of big data.

  • Planning a Hadoop 2.0 cluster
  • Cluster sizing, hardware
  • Network and software considerations
  • Popular Hadoop distributions
  • Workload and usage patterns
  • Industry recommendations

Hadoop 2.0 and features


Learning Objectives: In this module, you will learn more about the new features of Hadoop 2.0, HDFS High Availability, YARN framework and job execution flow, MRv2, federation, limitations of Hadoop 1.x and setting up Hadoop 2.0 Cluster setup in pseudo-distributed and distributed mode.

  • Limitations of Hadoop 1.x
  • Features of Hadoop 2.0
  • YARN framework
  • MRv2
  • Hadoop high availability and federation
  • YARN ecosystem and Hadoop 2.0 Cluster setup

Setting up Hadoop 2.X with highly availability and upgrading Hadoop


Learning Objectives: In this module, you will learn to setup Hadoop 2 with high availability, upgrading from v1 to v2, importing data from RDBMS into HDFS, understand why Oozie, Hive, and HBase are used and working on the components.

  • Configuring Hadoop 2 with high availability
  • upgrading to Hadoop 2
  • working with Sqoop
  • understanding Oozie
  • working with Hive
  • working with HBase

Project: Cloudera manager and Cluster setup, Overview on Kerberos


Learning Objectives: In this module, you will learn about Cloudera manager to setup Cluster, optimizations of Hadoop/Hbase/Hive performance parameters and understand the basics on Kerberos. You will learn to setup Pig to use in local/distributed mode to perform data analytics.

  • Cloudera manager and cluster setup
  • Hive administration
  • HBase architecture
  • HBase setup, Hadoop/Hive/HBase performance optimization
  • Pig setup and working with a grunt, why Kerberos and how it helps


We are providing Hadoop Administration Online Training in Ameerpet Hyderabad. We are one of best Institute to provide Best High Quality Hadoop Administration online training all over India. The IT Professionals and Students from India and abroad who are unable to attend regular classes can attend our Hadoop Administration online training from their home in their convenient timings. For more details on Hadoop Administration Online Training please call to 9290971883, / 9247461324, or drop a mail to revanthonlinetraining@gmail.com

Hadoop Administration online training institute address : B1, 3rd Floor, Eureka Court, Near Image Hospital, Ameerpet, Hyderabad, India


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