APACHE HADOOP FOR SYSTEMS ADMINISTRATORS – GTBD2

 

UPCOMING TRAINING EVENTS

GALWAY | Nov 29th to Dec 1st 2016 | CONTACT US FOR BOOKINGS

 

Course Description

This course covers the essentials of deploying and managing an Apache™ Hadoop® cluster. The course is lab intensive with each participant creating their own Hadoop cluster using either the CDH (Cloudera’s Distribution, including Apache Hadoop) or Hortonworks Data Platform stacks. Core Hadoop services are explored in depth with emphasis on troubleshooting and recovering from common cluster failures. The fundamentals of related services such as Ambari, Zookeeper, Pig, Hive, HBase, Sqoop, Flume, and Oozie are also covered. The course is approximately 60% lecture and 40% labs.

Supported Distributions:

Red Hat Enterprise Linux 7

Delivery Platform:

Hortonworks Data Platform Stack

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Duration

3 days

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Target Audience

General audience including business and technology team leadership.

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Course Prerequisites

Qualified participants should be comfortable with the Linux commands and have some systems administration experience, but do not need previous Hadoop experience

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Suggested Follow on Courses

There are a number of options of suitable follow-on courses, depending on your business needs. Please contact us for further details.

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Course Content

1. Hadoop Overview

  1. Data Analysis
  2. Big Data
  3. Origins of Hadoop
  4. Hadoop Marketplace
  5. Hadoop Core
  6. Hadoop Ecosystem:
  7. Hadoop Ecosystem (cont):
  8. Hadoop Ecosystem (cont):
  9. Hadoop Ecosystem (cont):
  10. Hadoop Ecosystem (cont):
  11. Cluster Architecture
  12. Hardware/Software Requirements
  13. Running Commands on Multiple Systems

LAB TASKS

  1. Running Commands on Multiple Hosts
  2. Preparing to Install Hadoop

 

2. HDFS

  1. Design Goals
  2. Design
  3. Blocks
  4. Block Replication
  5. Namenode Daemon
  6. Secondary Namenode Daemon
  7. Datanode Daemon
  8. Accessing HDFS
  9. Permissions and Users
  10. Adding and Removing Datanodes
  11. Balancing

LAB TASKS

  1. Single Node HDFS
  2. Multi‐node HDFS
  3. Files and HDFS
  4. Managing and Maintaining HDFS

 

3. YARN

  1. YARN Design Goals
  2. YARN Architecture
  3. Resource Manager
  4. Node Manager
  5. Containers
  6. YARN: Other Important Features
  7. Slider

LAB TASKS

  1. YARN

 

4. MAPREDUCE

  1. MapReduce
  2. Terminology and Data Flow

LAB TASKS

  1. Mapreduce

 

5. INSTALLING HADOOP WITH AMBARI LAB TASKS

  1. CDH Uninstall
  2. Installing Hadoop with Ambari
  3. Tez

 

6. DATA INGESTION

  1. Sqoop
  2. Flume
  3. Kafka

LAB TASKS

  1. Sqoop

 

7. DATA LINEAGE AND GOVERNANCE

  1. Falcon
  2. Atlas
  3. Oozie

 

8. DATA PROCESSING FRAMEWORKS

  1. The Bane of MapReduce
  2. Tez overview
  3. Pig
  4. Hive
  5. Spark
  6. Storm
  7. Solr
  8. Solr (cont)

LAB TASKS

  1. Pig

 

9. NOSQL IMPLEMENTATIONS

  1. HBase
  2. Phoenix

 

10. CLUSTER MANAGEMENT

1. Ambari Metrics System (AMS)

2. Zookeeper

 

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