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Big Data and Hadoop Administrator

simplilearn
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Description

Simplilearn is the World’s Largest Certification Training Provider, with over 400,000+ professionals trained globally
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Opinions

M

20/03/2014
What I would highlight The training was useful as it gave the insight on the overall Agile process and the best manner to prepare for the course. I am using Agile in my work and this has added additional items to my “tool kit” that I can start to implement at my work immediately. I enjoyed that the instructor took an Agile approach towards presenting the material.

Would you recommend this course? Yes.

Course programme

Course Preview Course Agenda
  • Big Data and Hadoop Administrator
    • Lesson 00 - Course Introduction
      • 0.1 Course Introduction
      • 0.2 Course Objectives
      • 0.3 Course Overview
      • 0.4 Course Overview (contd.)
      • 0.5 Course Prerequisites
      • 0.6 Value to Professionals
      • 0.7 Lessons Covered
      • 0.8 Concludes
    • Lesson 01 - Introduction to Big Data and Hadoop
      • 1.1 Introduction to Big Data and Hadoop
      • 1.2 Objectives
      • 1.3 Introduction
      • 1.4 Types Of Data
      • 1.5 Characteristics Of Big Data
      • 1.6 Appeal Of Big Data Technology
      • 1.7 Business Benefits Of Big Data Technology
      • 1.8 Business Benefits Of Big Data Technology (contd.)
      • 1.9 Traditional IT Analytics Approach
      • 1.10 Traditional IT Analytics Approach (contd.)
      • 1.11 Big Data Technology Platform For Discovery And Exploration
      • 1.12 Big Data Technology Platform For Discovery And Exploration (contd.)
      • 1.13 Big Data Technology Capabilities
      • 1.14 Big Data And Use Cases
      • 1.15 Challenges Of Big Data
      • 1.16 Introduction To Hadoop
      • 1.17 Hadoop And Traditional Rdbms
      • 1.18 History And Milestones Of Hadoop
      • 1.19 Hadoop Core Services
      • 1.20 Hdfs Architecture
      • 1.21 Organizations Using Hadoop
      • 1.22 Quiz
      • 1.23 Summary
      • 1.24 Conclusion
    • Lesson 02 - Planning Hadoop Cluster
      • 2.1 Planning Hadoop Cluster
      • 2.2 Objectives
      • 2.3 Overview of Hadoop Cluster
      • 2.4 Architecture of Hadoop Cluster
      • 2.5 Architecture of Hadoop Cluster (contd.)
      • 2.6 Architecture of Hadoop Cluster-Illustration
      • 2.7 Workflow of Hadoop Cluster
      • 2.8 HDFS Writes
      • 2.9 HDFS Writes-Example
      • 2.10 Preparing for HDFS Writes
      • 2.11 Pipelined HDFS Write
      • 2.12 NameNode
      • 2.13 NameNode Functionality
      • 2.14 Replicating Missing Replicas
      • 2.15 HDFS Reads
      • 2.16 Unbalanced Cluster
      • 2.17 Balancer Utility
      • 2.18 Factors for Planning Hadoop Cluster
      • 2.19 Hardware and Network Configurations-Slave
      • 2.20 Hardware and Network Configurations-Master
      • 2.21 Network Topology for Hadoop Cluster
      • 2.22 Network Topology for Hadoop Cluster (contd.)
      • 2.23 Topology and Components of Hadoop Cluster
      • 2.24 Cluster Management Commands
      • 2.25 Cluster Management-Illustration
      • 2.26 Quiz
      • 2.27 Summary
      • 2.28 Conclusion
    • Lesson 03 - Hadoop Installation and Configuration
      • 3.1 Hadoop Installation and Configuration
      • 3.2 Objectives
      • 3.3 Ubuntu Server-Introduction
      • 3.4 Installation of Ubuntu Server 12.4
      • 3.5 Business Scenario
      • 3.6 Demo Install Ubuntu Server 12.4
      • 3.7 Demo Summary
      • 3.8 Hadoop Installation
      • 3.9 Hadoop Installation-Prerequisites
      • 3.10 Hadoop Installation-Step 1
      • 3.11 Hadoop Installation-Step 2
      • 3.12 Hadoop Installation-Step 3
      • 3.13 Hadoop Installation-Step 4
      • 3.14 Hadoop Installation-Step 5
      • 3.15 Hadoop Installation-Step 6
      • 3.16 Hadoop Installation-Step 7
      • 3.17 Hadoop Installation-Step 7 (contd.)
      • 3.18 Hadoop Installation-Step 8
      • 3.19 Hadoop Installation-Step 8 (contd.)
      • 3.20 Hadoop Installation-Step 8 (contd.)
      • 3.21 Hadoop Installation-Step 9
      • 3.22 Hadoop Installation-Step 9 (contd.)
      • 3.23 Hadoop Installation-Step 10
      • 3.24 Hadoop Installation-Step 10 (contd.)
      • 3.25 Hadoop Installation-Step 11
      • 3.26 Hadoop Installation-Step 12
      • 3.27 Hadoop Installation-Step 12 (contd.)
      • 3.28 Demo Hadoop 1 . 0 in Ubuntu Server 12.4
      • 3.29 Demo Summary
      • 3.30 Hadoop Multi-Node Installation-Prerequisites
      • 3.31 Steps for Hadoop Multi-Node Installation
      • 3.32 Hadoop Multi-Node Installation-Steps 1 and 2
      • 3.33 Hadoop Multi-Node Installation-Step 3
      • 3.34 Hadoop Multi-Node Installation-Step 3 (contd.)
      • 3.35 Hadoop Multi-Node Installation-Step 4
      • 3.36 Hadoop Multi-Node Installation-Step 4 (contd.)
      • 3.37 Hadoop Multi-Node Installation-Step 4 (contd.)
      • 3.38 Single-Node Cluster vs Multi-Node Cluster
      • 3.39 Demo Create a Clone of Hadoop Virtual Machine
      • 3.40 Demo Summary
      • 3.41 Demo Perform Clustering of the Hadoop Environment
      • 3.42 Demo Summary
      • 3.43 Demo Install Hadoop 2. in Ubuntu Server 12.4
      • 3.44 Demo Summary
      • 3.45 Quiz
      • 3.46 Summary
      • 3.47 Conclusion
    • Lesson 04 - Advanced Cluster Configuration Features
      • 4.1 Advanced Cluster Configuration Features
      • 4.2 Objectives
      • 4.3 Hadoop Configuration Overview
      • 4.4 Types of Configuration Files
      • 4.5 Important Configuration Files
      • 4.6 Important Configuration Files (contd.)
      • 4.7 Configuration Parameters and Values
      • 4.8 Hadoop Cluster Configuration Parameters and Values
      • 4.9 Hadoop Cluster Configuration Parameters and Values (contd.)
      • 4.10 Hadoop Map Reduce Configuration Parameters and Values
      • 4.11 Prerequisites for Installing Hadoop
      • 4.12 Hadoop Environment Setup
      • 4.13 Include and Exclude Configuration Files
      • 4.14 Business Scenario
      • 4.15 Demo-Configuration of Hadoop Settings
      • 4.16 Demo summary
      • 4.17 Quiz
      • 4.18 Summary
      • 4.19 Conclusion
    • Lesson 05 - Hadoop Distributed File System
      • 5.1 Hadoop Distributed File System
      • 5.2 Objectives
      • 5.3 Introduction to Hadoop Distributed File System
      • 5.4 Goals of HDFS
      • 5.5 HDFS Architecture
      • 5.6 Design of HDFS
      • 5.7 HDFS Concept
      • 5.8 Hadoop Storage Mechanism
      • 5.9 Measures of Capacity Execution
      • 5.10 HDFS Storage Architecture Heterogeneous Storage
      • 5.11 HDFS Storage Architecture Illustration
      • 5.12 HDFS Rack Awareness
      • 5.13 HDFS Writes Example
      • 5.14 HDFS Reads
      • 5.15 Important Commands of HDFS
      • 5.16 Important Commands of HDFS (contd.)
      • 5.17 Types of HDFS Commands
      • 5.18 User Commands
      • 5.19 User Commands (contd.)
      • 5.20 Administrator Commands
      • 5.21 Administrator Commands (contd)
      • 5.22 Business Scenario
      • 5.23 Demo-HDFS
      • 5.24 Demo Summary
      • 5.25 Introduction to Sqoop
      • 5.26 Sqoop Illustration
      • 5.27 How Sqoop Works
      • 5.28 Prerequisites for Sqoop Installation
      • 5.29 Installing and Configuring Sqoop
      • 5.30 Installing and Configuring Sqoop (contd.)
      • 5.31 Installing and Configuring Sqoop (contd.)
      • 5.32 Importing Data from MySQL
      • 5.33 Business Scenario
      • 5.34 Demo-Install Sqoop
      • 5.35 Demo Summary
      • 5.36 Quiz
      • 5.37 Summary
      • 5.38 Conclusion
    • Lesson 06 - Overview of MapReduce and YARN
      • 6.1 Overview of MapReduce and YARN
      • 6.2 Objectives
      • 6.3 MapReduce Introduction
      • 6.4 Concepts of MapReduce
      • 6.5 History of MapReduce
      • 6.6 Automatic Parallel Execution in MapReduce
      • 6.7 MapReduce Framework
      • 6.8 How Map and Reduce Work Together
      • 6.9 MapReduce Example
      • 6.10 Workflow of MapReduce
      • 6.11 Characteristics of MapReduce
      • 6.12 Development and Libraries of MapReduce
      • 6.13 MapReduce Failure and Recovery
      • 6.14 Introduction to YARN
      • 6.15 Need for YARN
      • 6.16 Benefits of YARN
      • 6.17 YARN Architecture
      • 6.18 YARN Architecture Illustration
      • 6.19 YARN Daemons
      • 6.20 YARN Installation
      • 6.21 YARN Configuration
      • 6.22 Working with YARN and YARN Web UI
      • 6.23 Working with YARN and YARN Web UI (contd.)
      • 6.24 Quiz
      • 6.25 Summary
      • 6.26 Conclusion
    • Lesson 07 - Important Hadoop Components
      • 7.1 Important Hadoop Components
      • 7.2 Objectives
      • 7.3 Hive
      • 7.4 Hive vs. Other Traditional Databases
      • 7.5 Hive Data Types
      • 7.6 Prerequisites for Hive
      • 7.7 Installing Hive
      • 7.8 Installing Hive from Tarball
      • 7.9 Configuring Hive
      • 7.10 Hive site
      • 7.11 Hive default . xml . template
      • 7.12 Log Files
      • 7.13 Hive Configuration Variables
      • 7.14 Hive Configuration Variables (contd.)
      • 7.15 Hive Configuration Variables Used to Interact with Hadoop
      • 7.16 Hive Configuration Variables Used to Interact with Hadoop (contd.)
      • 7.17 Business Scenario
      • 7.18 Demo-Install Hive
      • 7.19 Demo summary
      • 7.20 Pig
      • 7.21 Prerequisites for Pig
      • 7.22 Installing Pig
      • 7.23 Useful Commands for Pig
      • 7.24 Configuring Pig
      • 7.25 Business Scenario
      • 7.26 Demo-Install Pig
      • 7.27 Demo Summary
      • 7.28 Impala
      • 7.29 Installing and Configuring Impala
      • 7.30 Quiz
      • 7.31 Summary
      • 7.32 conclusion
    • Lesson 08 - Hadoop Administration and Maintenance
      • 8.1 Hadoop Administration and Maintenance
      • 8.2 Objectives
      • 8.3 Structural NameNode Formation and Naming Conventions
      • 8.4 Structural DataNode Formation and Naming Conventions
      • 8.5 File System Image and Edit Log
      • 8.6 Checkpoint Procedure
      • 8.7 The Checkpoint Procedure (contd.)
      • 8.8 NameNode Failure and Recovery Procedure
      • 8.9 Safe Mode
      • 8.10 Metadata and Data Backup
      • 8.11 Problems for Hadoop Administrators
      • 8.12 Problems for Hadoop Administrators (contd.)
      • 8.13 Solutions for Problems
      • 8.14 Adding Nodes
      • 8.15 Adding Nodes (contd.)
      • 8.16 Removing Nodes
      • 8.17 Quiz
      • 8.18 Summary
      • 8.19 Conclusion
    • Lesson 09 - Hadoop Ecosystem Components
      • 9.1 Hadoop Ecosystem Components
      • 9.2 Objectives
      • 9.3 Overview of Ganglia
      • 9.4 Components of Ganglia
      • 9.5 Installation of Ganglia for Hadoop Server
      • 9.6 Using Ganglia for Graphs
      • 9.7 Using Ganglia for Graphs (contd)
      • 9.8 Overview of Nagios
      • 9.9 Installing Nagios
      • 9.10 Installing Nagios Building from Source Method
      • 9.11 Configuring Nagios for-Hadoop Alerts
      • 9.12 Configuring Nagios for Hadoop Alerts (contd.)
      • 9.13 Introduction to Sqoop
      • 9.14 Advantages of Sqoop
      • 9.15 Installing and Configuring Sqoop
      • 9.16 Installing and Configuring Sqoop (contd.)
      • 9.17 Importing Data from MySql to Hive using Sqoop
      • 9.18 Other Ecosystem Components
      • 9.19 Oozie
      • 9.20 How Oozie Works
      • 9.21 Avro
      • 9.22 Thrift
      • 9.23 Rest
      • 9.24 Mahout
      • 9.25 Apache Cassandra
      • 9.26 Cassandra (contd.)
      • 9.27 Yarn
      • 9.28 MR2
      • 9.29 Hadoop Security
      • 9.30 Kerberos and Hadoop
      • 9.31 Importance of Hadoop Security
      • 9.32 Hadoop Security System Concepts
      • 9.33 Hadoop Integral Security Layer Authentication
      • 9.34 Hadoop Integral Security Layer Authorization
      • 9.35 Hadoop Integral Security Layer Encryption
      • 9.36 OS Layer Security
      • 9.37 Data Transfer and Integration Layer Security
      • 9.38 Data Transfer and Integration Layer Security (contd.)
      • 9.39 What is Kerberos and How it Works
      • 9.40 Configuring Kerberos Security
      • 9.41 Quiz
      • 9.42 Summary
      • 9.43 Summary (contd)
      • 9.44 Thank You

Additional information

  • What is this course about?

    Big Data and Hadoop Administrator Certification Training from Simplilearn equips you to take up Hadoop Administrator responsibilities in provisioning, installing, configuring, monitoring, maintaining and securing Hadoop and Hadoop Eco system components.

    Training is designed to ensure that you are job ready for the role of Hadoop Administrator with implementation of real life Hadoop Administration industry projects spanned across 3 months.

    This training is developed to give you a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster.

  • What are the course objectives?

    With Certification in Hadoop Administration training, you will be able to -

    • Master the understanding of Hadoop and Hadoop Administration eco system components
    • Plan Hadoop Clusters with installation and configuration of Hadoop as well as configuration of single node and multi node Hadoop Clusters
    • Become proficient in HDFS and Sqoop with the help of Demos and hands on Lab exercises.
    • Install & configure YARN with gaining in depth understanding of Map Reduce and YARN architecture
    • Become expert in recovering from node failures and troubleshoot common Hadoop cluster issues
    • Install and configure Hadoop Eco system components such as Hive, Pig, Impala, Ganglia, Nagios, Sqoop
    • Expertise in setup, configuration and management of security for Hadoop clusters using Kerbero

  • Who should do this course?

    • Systems administrators and IT managers
    • IT administrators and operators
    • IT Systems Engineer
    • Data Engineer
    • Data Analytics Administrator
    • Cloud Systems Administrator
    • Web Engineer

  • What are the prerequisites for the course?

    Fundamental knowledge of any programming language and Linux environment. Participants should know how to navigate and modify files within a Linux environment. Existing knowledge of Hadoop & Java is not required.


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