Customized Onsite Training

4
Days
  • Customized Content
  • For Groups of 5+
  • Online or On-location
  • Expert Instructors
Request Class or call 1-877-932-8228
Overview

In this Hadoop Administration training class, students learn all about working with Hadoop and HDFS.

Goals
  1. Learn the fundamental concepts of Hadoop.
  2. Learn to plan your Hadoop cluster.
  3. Learn HDFS features.
  4. Learn how to get data into HDFS.
  5. Learn to work with MapReduce.
  6. Learn installation and configuration of Hadoop.
  7. Learn cluster maintenance.
Outline
  1. Hadoop Overview
    1. What is Big Data?
    2. How did we get to this point?
    3. How does Hadoop compare to a relational database system?
    4. Big Data Introduction
    5. History
    6. Comparison to Relational Databases
    7. Hadoop Ecosystem
  2. HDFS
    1. Architecture/Concepts
    2. Access
    3. Namenodes
    4. Filesystem Shell
    5. Accessing HDFS with Java
    6. Reading/Writing/Browsing file system
  3. HBASE
    1. Overview
    2. Architecture
    3. Data Model
    4. Installation and Shell
    5. Access via Java API
    6. Administration access via Java
    7. Scan API
    8. Filters
    9. Storage Model
    10. Table Design
  4. Map Reduce on YARN
    1. Introduction
    2. Processing Model
    3. Command line tools
    4. MapReduce framework
    5. Submitting MapReduce Jobs
    6. Writing MapReduce jobs in Java
    7. MapReduce Theory
    8. Distributive Cache
    9. Speculative Executin
    10. YARN Components
    11. Counters
    12. Details of MapReduce Job Execution
  5. Hadoop Streaming
    1. Implementing a streaming job
    2. Counters in streaming jobs
    3. Contrast with Java Jobs
  6. MapReduce Workflows
    1. Problem decomposition into MapReduce Jobs
    2. Coding workflows
    3. Using the JobControl Class
  7. Oozie
    1. Oozie Installation
    2. Writing Oozie workflows
    3. Deploying and running Oozie jobs
  8. Pig
    1. Installation
    2. Pig Latin
    3. Writing Pig Scripts
    4. User Defined functions
    5. Data set joins
  9. Hive
    1. Installation
    2. Table creation and deletion
    3. Partitioning
    4. Loading data into Hive
    5. Joins
    6. Bucketing
Class Materials

Each student in our Live Online and our Onsite classes receives a comprehensive set of materials, including course notes and all the class examples.

Class Prerequisites

Experience in the following is required for this Hadoop class:

  • Basic Java Knowledge.

Experience in the following would be useful for this Hadoop class:

  • Experience with Eclipse.
Preparing for Class

No cancelation for low enrollment

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Contact Us or call 1-877-932-8228