HDInsight Essentials - Second Edition

By Rajesh Nadipalli

About This Book

• Learn how to quickly provision a Hadoop cluster using Windows Azure Cloud Services
• Build an end-to-end application for a big data problem using open source software
• Discover more about modern data architecture with this guide, to help you understand the transition from legacy relational Enterprise Data Warehouse

Who This Book Is For

If you want to discover one of the latest tools designed to produce stunning Big Data insights, this book features everything you need to get to grips with your data. Whether you are a data architect, developer, or a business strategist, HDInsight adds value in everything from development, administration, and reporting.

• Language: English
• Publisher: Packt Publishing
• Release date: Jan 27, 2015
• ISBN: 9781784396664

Book preview

Table of Contents

HDInsight Essentials Second Edition

Credits

About the Author

About the Reviewers

www.PacktPub.com

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Free access for Packt account holders

Instant updates on new Packt books

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Errata

Piracy

Questions

1. Hadoop and HDInsight in a Heartbeat

Data is everywhere

Business value of big data

Hadoop concepts

Brief history of Hadoop

Core components

Hadoop cluster layout

HDFS overview

Writing a file to HDFS

Reading a file from HDFS

HDFS basic commands

YARN overview

YARN application life cycle

YARN workloads

Hadoop distributions

HDInsight overview

HDInsight and Hadoop relationship

Hadoop on Windows deployment options

Microsoft Azure HDInsight Service

HDInsight Emulator

Hortonworks Data Platform (HDP) for Windows

Summary

2. Enterprise Data Lake using HDInsight

Enterprise Data Warehouse architecture

Source systems

Data warehouse

Storage

Processing

User access

Provisioning and monitoring

Data governance and security

Pain points of EDW

The next generation Hadoop-based Enterprise data architecture

Source systems

Data Lake

Storage

Processing

User access

Provisioning and monitoring

Data governance, security, and metadata

Journey to your Data Lake dream

Ingestion and organization

Transformation (rules driven)

Access, analyze, and report

Tools and technology for Hadoop ecosystem

Use case powered by Microsoft HDInsight

Problem statement

Solution

Source systems

Storage

Processing

User access

Benefits

Summary

3. HDInsight Service on Azure

Registering for an Azure account

Azure storage

Provisioning an HDInsight cluster

Cluster topology

Provisioning using Azure PowerShell

Creating a storage container

Provisioning a new HDInsight cluster

HDInsight management dashboard

Dashboard

Monitor

Configuration

Exploring clusters using the remote desktop

Running a sample MapReduce

Deleting the cluster

HDInsight Emulator for the development

Installing HDInsight Emulator

Installation verification

Using HDInsight Emulator

Summary

4. Administering Your HDInsight Cluster

Monitoring cluster health

Name Node status

The Name Node Overview page

Datanode Status

Utilities and logs

Hadoop Service Availability

YARN Application Status

Azure storage management

Configuring your storage account

Monitoring your storage account

Managing access keys

Deleting your storage account

Azure PowerShell

Access Azure Blob storage using Azure PowerShell

Summary

5. Ingest and Organize Data Lake

End-to-end Data Lake solution

Ingesting to Data Lake using HDFS command

Connecting to a Hadoop client

Getting your files on the local storage

Transferring to HDFS

Loading data to Azure Blob storage using Azure PowerShell

Loading files to Data Lake using GUI tools

Storage access keys

Storage tools

CloudXplorer

Key benefits

Registering your storage account

Uploading files to your Blob storage

Using Sqoop to move data from RDBMS to Data Lake

Key benefits

Two modes of using Sqoop

Using Sqoop to import data (SQL to Hadoop)

Organizing your Data Lake in HDFS

Managing file metadata using HCatalog

Key benefits

Using HCatalog Command Line to create tables

Summary

6. Transform Data in the Data Lake

Transformation overview

Tools for transforming data in Data Lake

HCatalog

Persisting HCatalog metastore in a SQL database

Apache Hive

Hive architecture

Starting Hive in HDInsight

Basic Hive commands

Apache Pig

Pig architecture

Starting Pig in HDInsight node

Basic Pig commands

Pig or Hive

MapReduce

The mapper code

The reducer code

The driver code

Executing MapReduce on HDInsight

Azure PowerShell for execution of Hadoop jobs

Transformation for the OTP project

Cleaning data using Pig

Executing Pig script

Registering a refined and aggregate table using Hive

Executing Hive script

Reviewing results

Other tools used for transformation

Oozie

Spark

Summary

7. Analyze and Report from Data Lake

Data access overview

Analysis using Excel and Microsoft Hive ODBC driver

Prerequisites

Step 1 – installing the Microsoft Hive ODBC driver

Step 2 – creating Hive ODBC Data Source

Step 3 – importing data to Excel

Analysis using Excel Power Query

Prerequisites

Step 1 – installing the Microsoft Power Query for Excel

Step 2 – importing Azure Blob storage data into Excel

Step 3 – analyzing data using Excel

Other BI features in Excel

PowerPivot

Power View and Power Map

Step 1 – importing Azure Blob storage data into Excel

Step 2 – launch map view

Step 3 – configure the map

Power BI Catalog

Ad hoc analysis using Hive

Other alternatives for analysis

RHadoop

Apache Giraph

Apache Mahout

Azure Machine Learning

Summary

8. HDInsight 3.1 New Features

HBase

HBase positioning in Data Lake and use cases

Provisioning HDInsight HBase cluster

Creating a sample HBase schema

Designing the airline on-time performance table

Connecting to HBase using the HBase shell

Creating an HBase table

Loading data to the HBase table

Querying data from the HBase table

HBase additional information

Storm

Storm positioning in Data Lake

Storm key concepts

Provisioning HDInsight Storm cluster

Running a sample Storm topology

Connecting to Storm using Storm shell

Running the Storm Wordcount topology

Monitoring status of the Wordcount topology

Additional information on Storm

Apache Tez

Summary

9. Strategy for a Successful Data Lake Implementation

Challenges on building a production Data Lake

The success path for a production Data Lake

Identifying the big data problem

Proof of technology for Data Lake

Form a Data Lake Center of Excellence

Executive sponsors

Data Lake consumers

Development

Operations and infrastructure

Architectural considerations

Extensible and modular

Metadata-driven solution

Integration strategy

Security

Online resources

Summary

Index

HDInsight Essentials Second Edition

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HDInsight Essentials Second Edition

Copyright © 2015 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: September 2013

Second edition: January 2015

Production reference: 1200115

Published by Packt Publishing Ltd.

Livery Place

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Birmingham B3 2PB, UK.

ISBN 978-1-78439-942-9

www.packtpub.com

Credits

Author

Rajesh Nadipalli

Reviewers

Simon Elliston Ball

Anindita Basak

Rami Vemula

Commissioning Editor

Taron Pereira

Acquisition Editor

Owen Roberts

Content Development Editor

Rohit Kumar Singh

Technical Editors

Madhuri Das

Taabish Khan

Copy Editor

Rashmi Sawant

Project Coordinator

Mary Alex

Proofreaders

Ting Baker

Ameesha Green

Indexer

Rekha Nair

Production Coordinator

Melwyn D'sa

Cover Work

Melwyn D'sa

About the Author

Rajesh Nadipalli currently manages software architecture and delivery of Zaloni's Bedrock Data Management Platform, which enables customers to quickly and easily realize true Hadoop-based Enterprise Data Lakes. Rajesh is also an instructor and a content provider for Hadoop training, including Hadoop development, Hive, Pig, and HBase. In his previous role as a senior solutions architect, he evaluated big data goals for his clients, recommended a target state architecture, and conducted proof of concepts and production implementation. His clients include Verizon, American Express, NetApp, Cisco, EMC, and UnitedHealth Group.

Prior to Zaloni, Rajesh worked for Cisco Systems for 12 years and held a technical leadership position. His key focus areas have been data management, enterprise architecture, business intelligence, data warehousing, and Extract Transform Load (ETL). He has demonstrated success by delivering scalable data management and BI solutions that empower business to make informed decisions.

Rajesh authored the first version of the book HDInsight Essentials, Packt Publishing, released in September 2013, the first book in print for HDInsight, providing data architects, developers, and managers with an introduction to the new Hadoop distribution from Microsoft.

He has over 18 years of IT experience. He holds an MBA from North Carolina State University and a BSc degree in Electronics and Electrical from the University of Mumbai, India.

I would like to thank my family for their unconditional love, support, and patience during the entire process.

To my friends and coworkers at Zaloni, thank you for inspiring and encouraging me.

And finally a shout-out to all the folks at Packt Publishing for being really professional.

About the Reviewers

Simon Elliston Ball is a solutions engineer at Hortonworks, where he helps a wide range of companies get the best out of Hadoop. Before that, he was the head of big data at Red Gate, creating tools to make HDInsight and Hadoop easier to work with. He has also spoken extensively on big data and NoSQL at conferences around the world.

Anindita Basak works as a big data cloud consultant and a big data Hadoop trainer and is highly enthusiastic about Microsoft Azure and HDInsight along with Hadoop open source ecosystem. She works as a specialist for Fortune 500 brands including cloud and big data based companies in the US. She has been playing with Hadoop on Azure since the incubation phase (http://www.hadooponazure.com). Previously, she worked as a module lead for the Alten group and as a senior system analyst at Sonata Software Limited, India, in the Azure Professional Direct Delivery group of Microsoft. She worked as a senior software engineer on implementation and migration of various enterprise applications on the Azure cloud in healthcare, retail, and financial domains. She started her journey with Microsoft Azure in the Microsoft Cloud Integration Engineering (CIE) team and worked as a support engineer in Microsoft India (R&D) Pvt. Ltd.

With more than 6 years of experience in the Microsoft .NET technology stack, she is solely focused on big data cloud and data science. As a Most Valued Blogger, she loves to share her technical experience and expertise through her blog at http://anindita9.wordpress.com and http://anindita9.azurewebsites.net. You can find more about her on her LinkedIn page and you can follow her at @imcuteani on Twitter.

She recently worked as a technical reviewer for the books HDInsight Essentials and Microsoft Tabular Modeling Cookbook, both by Packt Publishing. She is currently working on Hadoop Essentials, also by Packt Publishing.

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