Hadoop Administration Online Training Classes

HADOOP Administration Online Training

Course Modules:

BASIC HADOOP

1. Introduction and Overview of Hadoop
2. Hadoop Distributed FileSystem (HDFS)
3. HBase - The Hadoop Database
4. Map/Reduce 2.0/YARN
5. MapReduce Workflows
6. Pig
7. Hive
8. Sqoop
9. Putting it all together

ADVANCED HADOOP

1. Integrating Hadoop Into The Workflow
2. Delving Deeper Into The Hadoop API
3. Common Map Reduce Algorithms
4. Using Hive and Pig
5. Practical Development Tips and Techniques
6. More Advanced Map Reduce Programming
7. Joining Data Sets in Map Reduce
8. Graph Manipulation in Hadoop
9. Creating Workflows With Oozie
10. HANDS ON EXCERCISE

Attendees also learn:

1. Resume Preparation Guidelines and Tips
2. Mock Interviews and Interview Preparation Tips

Topics Covered

BASIC HADOOP

Introduction and Overview of Hadoop

• What is Hadoop?
• History of Hadoop.
• Building Blocks - Hadoop Eco-System.
• Who is behind Hadoop?
• What Hadoop is good for and what it is not?

Hadoop Distributed FileSystem (HDFS)

• HDFS Overview and Architecture
• HDFS Installation
• HDFS Use Cases
• Hadoop FileSystem Shell
• FileSystem Java API
• Hadoop Configuration

HBase - The Hadoop Database

• HBase Overview and Architecture
• HBase Installation
• HBase Shell
• Java Client API
• Java Administrative API
• Filters
• Scan Caching and Batching
• Key Design
• Table Design

Map/Reduce 2.0/YARN

• MapReduce 2.0 and YARN Overview
• MapReduce 2.0 and YARN Architecture
• Installation
• YARN and MapReduce Command Line Tools
• Developing MapReduce Jobs
• Input and Output Formats
• HDFS and HBase as Source and Sink
• Job Configuration
• Job Submission and Monitoring
• Anatomy of Mappers, Reducers, Combiners and Partitioners/li>
• Anatomy of Job Execution on YARN
• Distributed Cache
• Hadoop Streaming

MapReduce Workflows

• Decomposing Problems into MapReduce Workflow
• Using Job Control
• Oozie Introduction and Architecture
• Oozie Installation
• Developing, deploying, and Executing Oozie Workflows

Pig

• Pig Overview
• Installation
• Pig Latin
• Developing Pig Scripts
• Processing Big Data with Pig
• Joining data-sets with Pig

Hive

• Hive Overview
• Installation
• Hive QL

Sqoop

• Introduction
• Sqoop Tools
• Sqoop Import
• Sqoop Import all tables
• Sqoop Export
• Sqoop Job
• Sqoop metastore
• Sqoop Eval
• Sqoop Codegen
• Sqoop List Databases and List Tables
• Sqoop Create Hive Table

Putting it all together

• Distributed installations
• Best Practices

ADVANCED HADOOP:-

Outline:

Our Advanced Hadoop is an extension of Essential Hadoop Module designed with objective of in-depth coverage with case study illustration.

Integrating Hadoop into the Workflow

• Relational Database Management Systems
• Storage Systems
• Importing Data from RDBMSs With Sqoop
• Hands-on exercise
• Importing Real-Time Data with Flume
• Accessing HDFS Using FuseDFS and Hoop

Delving Deeper Into the Hadoop API

• More about ToolRunner
• Testing with MRUnit
• Reducing Intermediate Data With Combiners
• The configure and close methods for Map/Reduce Setup and Teardown
• Writing Partitioners for Better Load Balancing
• Hands-On Exercise
• Directly Accessing HDFS
• Using the Distributed Cache
• Hands-On Exercise

Common MapReduce Algorithms

• Sorting and Searching
• Indexing
• Machine Learning With Mahout
• Term Frequency - Inverse Document Frequency
• Word Co-Occurrence
• Hands-On Exercise

Using Hive and Pig

• Hive Basics
• Pig Basics
• Hands-on exercise

Practical Development Tips and Techniques

• Debugging MapReduce Code
• Using LocalJobRunner Mode For Easier Debugging
• Retrieving Job Information with Counters
• Logging
• Splittable File Formats
• Determining the Optimal Number of Reducers
• Map-Only MapReduce Jobs
• Hands-On-Exercise

More Advanced MapReduce Programming

• Custom Writables and WritableComparables
• Saving Binary Data using SequenceFiles and Avro Files
• Creating InputFormats and OutputFormats
• Hands-On Exercise

Joining Data Sets in MapReduce

• Map-Side Joins
• The Secondary Sort
• Reduce-Side Joins

Graph Manipulation in Hadoop

• Introduction to graph techniques
• Representing graphs in Hadoop
• Implementing a sample algorithm: Single Source Shortest Path

Creating Workflows with Oozie

• The Motivation for Oozie
• Oozie’s Workflow Definition Format
• HANDS ON EXERCISE