Hadoop For Dummies
Published on 21. March 2014
408 pages
978-1-118-65220-6 (ISBN)
Description
Let Hadoop For Dummies help harness the power of yourdata and rein in the information overload
Big data has become big business, and companies and organizationsof all sizes are struggling to find ways to retrieve valuableinformation from their massive data sets with becoming overwhelmed.Enter Hadoop and this easy-to-understand For Dummiesguide. Hadoop For Dummies helps readers understand thevalue of big data, make a business case for using Hadoop, navigatethe Hadoop ecosystem, and build and manage Hadoop applications andclusters.
* Explains the origins of Hadoop, its economic benefits, and itsfunctionality and practical applications
* Helps you find your way around the Hadoop ecosystem, programMapReduce, utilize design patterns, and get your Hadoop cluster upand running quickly and easily
* Details how to use Hadoop applications for data mining, webanalytics and personalization, large-scale text processing, datascience, and problem-solving
* Shows you how to improve the value of your Hadoop cluster,maximize your investment in Hadoop, and avoid common pitfalls whenbuilding your Hadoop cluster
From programmers challenged with building and maintainingaffordable, scaleable data systems to administrators who must dealwith huge volumes of information effectively and efficiently, thishow-to has something to help you with Hadoop.
Big data has become big business, and companies and organizationsof all sizes are struggling to find ways to retrieve valuableinformation from their massive data sets with becoming overwhelmed.Enter Hadoop and this easy-to-understand For Dummiesguide. Hadoop For Dummies helps readers understand thevalue of big data, make a business case for using Hadoop, navigatethe Hadoop ecosystem, and build and manage Hadoop applications andclusters.
* Explains the origins of Hadoop, its economic benefits, and itsfunctionality and practical applications
* Helps you find your way around the Hadoop ecosystem, programMapReduce, utilize design patterns, and get your Hadoop cluster upand running quickly and easily
* Details how to use Hadoop applications for data mining, webanalytics and personalization, large-scale text processing, datascience, and problem-solving
* Shows you how to improve the value of your Hadoop cluster,maximize your investment in Hadoop, and avoid common pitfalls whenbuilding your Hadoop cluster
From programmers challenged with building and maintainingaffordable, scaleable data systems to administrators who must dealwith huge volumes of information effectively and efficiently, thishow-to has something to help you with Hadoop.
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Dirk deRoos is the technical sales lead for IBM'sInfoSphere BigInsights. Paul C. Zikopoulos is the vicepresident of big data in the IBM Information Management division.Roman B. Melnyk, PhD is a senior member of the DB2Information Development team. Bruce Brown and RafaelCoss work with big data with IBM.
Content
Introduction 1
Part I: Getting Started with Hadoop 7
Chapter 1: Introducing Hadoop and Seeing What It's GoodFor 9
Chapter 2: Common Use Cases for Big Data in Hadoop 23
Chapter 3: Setting Up Your Hadoop Environment 41
Part II: How Hadoop Works 51
Chapter 4: Storing Data in Hadoop: The Hadoop Distributed FileSystem 53
Chapter 5: Reading and Writing Data 69
Chapter 6: MapReduce Programming 83
Chapter 7: Frameworks for Processing Data in Hadoop: YARN andMapReduce 103
Chapter 8: Pig: Hadoop Programming Made Easier 117
Chapter 9: Statistical Analysis in Hadoop 129
Chapter 10: Developing and Scheduling Application Workflows withOozie 139
Part III: Hadoop and Structured Data 155
Chapter 11: Hadoop and the Data Warehouse: Friends or Foes?157
Chapter 12: Extremely Big Tables: Storing Data in HBase 179
Chapter 13: Applying Structure to Hadoop Data with Hive 227
Chapter 14: Integrating Hadoop with Relational Databases UsingSqoop 269
Chapter 15: The Holy Grail: Native SQL Access to Hadoop Data303
Part IV: Administering and ConfiguringHadoop 313
Chapter 16: Deploying Hadoop 315
Chapter 17: Administering Your Hadoop Cluster 335
Part V: The Part of Tens 359
Chapter 18: Ten Hadoop Resources Worthy of a Bookmark 361
Chapter 19: Ten Reasons to Adopt Hadoop 371
Index 379
Part I: Getting Started with Hadoop 7
Chapter 1: Introducing Hadoop and Seeing What It's GoodFor 9
Chapter 2: Common Use Cases for Big Data in Hadoop 23
Chapter 3: Setting Up Your Hadoop Environment 41
Part II: How Hadoop Works 51
Chapter 4: Storing Data in Hadoop: The Hadoop Distributed FileSystem 53
Chapter 5: Reading and Writing Data 69
Chapter 6: MapReduce Programming 83
Chapter 7: Frameworks for Processing Data in Hadoop: YARN andMapReduce 103
Chapter 8: Pig: Hadoop Programming Made Easier 117
Chapter 9: Statistical Analysis in Hadoop 129
Chapter 10: Developing and Scheduling Application Workflows withOozie 139
Part III: Hadoop and Structured Data 155
Chapter 11: Hadoop and the Data Warehouse: Friends or Foes?157
Chapter 12: Extremely Big Tables: Storing Data in HBase 179
Chapter 13: Applying Structure to Hadoop Data with Hive 227
Chapter 14: Integrating Hadoop with Relational Databases UsingSqoop 269
Chapter 15: The Holy Grail: Native SQL Access to Hadoop Data303
Part IV: Administering and ConfiguringHadoop 313
Chapter 16: Deploying Hadoop 315
Chapter 17: Administering Your Hadoop Cluster 335
Part V: The Part of Tens 359
Chapter 18: Ten Hadoop Resources Worthy of a Bookmark 361
Chapter 19: Ten Reasons to Adopt Hadoop 371
Index 379
