Dirk deRoos is the technical sales lead for IBM’s InfoSphere BigInsights. Paul C. Zikopoulos is the vice president of big data in the IBM Information Management division. Roman B. Melnyk, PhD is a senior member of the DB2 Information Development team. Bruce Brown and Rafael Coss work with big data with IBM.

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• Introduction 1Part I: Getting Started with Hadoop 7Chapter 1: Introducing Hadoop and Seeing What It’s Good For 9Chapter 2: Common Use Cases for Big Data in Hadoop 23Chapter 3: Setting Up Your Hadoop Environment 41Part II: How Hadoop Works 51Chapter 4: Storing Data in Hadoop: The Hadoop Distributed File System 53Chapter 5: Reading and Writing Data 69Chapter 6: MapReduce Programming 83Chapter 7: Frameworks for Processing Data in Hadoop: YARN and MapReduce 103Chapter 8: Pig: Hadoop Programming Made Easier 117Chapter 9: Statistical Analysis in Hadoop 129Chapter 10: Developing and Scheduling Application Workflows with Oozie 139Part III: Hadoop and Structured Data 155Chapter 11: Hadoop and the Data Warehouse: Friends or Foes? 157Chapter 12: Extremely Big Tables: Storing Data in HBase 179Chapter 13: Applying Structure to Hadoop Data with Hive 227Chapter 14: Integrating Hadoop with Relational Databases Using Sqoop 269Chapter 15: The Holy Grail: Native SQL Access to Hadoop Data 303Part IV: Administering and Configuring Hadoop 313Chapter 16: Deploying Hadoop 315Chapter 17: Administering Your Hadoop Cluster 335Part V: The Part of Tens 359Chapter 18: Ten Hadoop Resources Worthy of a Bookmark 361Chapter 19: Ten Reasons to Adopt Hadoop 371Index 379

Dirk deRoos is the technical sales lead for IBM’s InfoSphere BigInsights. Paul C. Zikopoulos is the vice president of big data in the IBM Information Management division. Roman B. Melnyk, PhD is a senior member of the DB2 Information Development team. Bruce Brown and Rafael Coss work with big data with IBM.

Select Guide Rating

• Introduction 1Part I: Getting Started with Hadoop 7Chapter 1: Introducing Hadoop and Seeing What It’s Good For 9Chapter 2: Common Use Cases for Big Data in Hadoop 23Chapter 3: Setting Up Your Hadoop Environment 41Part II: How Hadoop Works 51Chapter 4: Storing Data in Hadoop: The Hadoop Distributed File System 53Chapter 5: Reading and Writing Data 69Chapter 6: MapReduce Programming 83Chapter 7: Frameworks for Processing Data in Hadoop: YARN and MapReduce 103Chapter 8: Pig: Hadoop Programming Made Easier 117Chapter 9: Statistical Analysis in Hadoop 129Chapter 10: Developing and Scheduling Application Workflows with Oozie 139Part III: Hadoop and Structured Data 155Chapter 11: Hadoop and the Data Warehouse: Friends or Foes? 157Chapter 12: Extremely Big Tables: Storing Data in HBase 179Chapter 13: Applying Structure to Hadoop Data with Hive 227Chapter 14: Integrating Hadoop with Relational Databases Using Sqoop 269Chapter 15: The Holy Grail: Native SQL Access to Hadoop Data 303Part IV: Administering and Configuring Hadoop 313Chapter 16: Deploying Hadoop 315Chapter 17: Administering Your Hadoop Cluster 335Part V: The Part of Tens 359Chapter 18: Ten Hadoop Resources Worthy of a Bookmark 361Chapter 19: Ten Reasons to Adopt Hadoop 371Index 379

Dirk deRoos is the technical sales lead for IBM’s InfoSphere BigInsights. Paul C. Zikopoulos is the vice president of big data in the IBM Information Management division. Roman B. Melnyk, PhD is a senior member of the DB2 Information Development team. Bruce Brown and Rafael Coss work with big data with IBM.

Select Guide Rating

• Introduction 1Part I: Getting Started with Hadoop 7Chapter 1: Introducing Hadoop and Seeing What It’s Good For 9Chapter 2: Common Use Cases for Big Data in Hadoop 23Chapter 3: Setting Up Your Hadoop Environment 41Part II: How Hadoop Works 51Chapter 4: Storing Data in Hadoop: The Hadoop Distributed File System 53Chapter 5: Reading and Writing Data 69Chapter 6: MapReduce Programming 83Chapter 7: Frameworks for Processing Data in Hadoop: YARN and MapReduce 103Chapter 8: Pig: Hadoop Programming Made Easier 117Chapter 9: Statistical Analysis in Hadoop 129Chapter 10: Developing and Scheduling Application Workflows with Oozie 139Part III: Hadoop and Structured Data 155Chapter 11: Hadoop and the Data Warehouse: Friends or Foes? 157Chapter 12: Extremely Big Tables: Storing Data in HBase 179Chapter 13: Applying Structure to Hadoop Data with Hive 227Chapter 14: Integrating Hadoop with Relational Databases Using Sqoop 269Chapter 15: The Holy Grail: Native SQL Access to Hadoop Data 303Part IV: Administering and Configuring Hadoop 313Chapter 16: Deploying Hadoop 315Chapter 17: Administering Your Hadoop Cluster 335Part V: The Part of Tens 359Chapter 18: Ten Hadoop Resources Worthy of a Bookmark 361Chapter 19: Ten Reasons to Adopt Hadoop 371Index 379