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Hadoop for dummies / By Dirk deRoss...[et.al.].

By: Contributor(s): Material type: TextTextLanguage: English Publication details: New Delhi Wiley India Pvt Ltd 2014Edition: 1Description: xii,394/2017ISBN:
  • 9788126550517
Subject(s): DDC classification:
  • 005.7681  1 DERD
Contents:
Introduction Part I: Getting Started with Hadoop Chapter 1: Introducing Hadoop and Seeing What It's Good For Chapter 2: Common Use Cases for Big Data in Hadoop Chapter 3: Setting Up Your Hadoop Environment Part II: How Hadoop Works Chapter 4: Storing Data in Hadoop: The Hadoop Distributed File System Chapter 5: Reading and Writing Data Chapter 6: MapReduce Programming Chapter 7: Frameworks for Processing Data in Hadoop: YARN and MapReduce Chapter 8: Pig: Hadoop Programming Made Easier Chapter 9: Statistical Analysis in Hadoop Chapter 10: Developing and Scheduling Application Workflows with Oozie Part III: Hadoop and Structured Data Chapter 11: Hadoop and the Data Warehouse: Friends or Foes? Chapter 12: Extremely Big Tables: Storing Data in HBase Chapter 13: Applying Structure to Hadoop Data with Hive Chapter 14: Integrating Hadoop with Relational Databases Using Sqoop Chapter 15: The Holy Grail: Native SQL Access to Hadoop Data Part IV: Administering and Configuring Hadoop Chapter 16: Deploying Hadoop Chapter 17: Administering Your Hadoop Cluster Part V: The Part of Tens Chapter 18: Ten Hadoop Resources Worthy of a Bookmark Chapter 19: Ten Reasons to Adopt Hadoop Index About the Author Roman B. Melnyk is a senior member of the DB2 Information Development team. Paul Zikopoulos is the executive for Technical Sales in IBM Information Management
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Item type Current library Collection Call number Status Barcode
Book Book St Aloysius Institute of Management & Information Technology Data Science MCA 005.7681 DERD (Browse shelf(Opens below)) Available MCA17365
Book Book St Aloysius Institute of Management & Information Technology MCA 005.7681 DERD (Browse shelf(Opens below)) Available MCA15270
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Introduction

Part I: Getting Started with Hadoop

Chapter 1: Introducing Hadoop and Seeing What It's Good For

Chapter 2: Common Use Cases for Big Data in Hadoop

Chapter 3: Setting Up Your Hadoop Environment

Part II: How Hadoop Works

Chapter 4: Storing Data in Hadoop: The Hadoop Distributed File System

Chapter 5: Reading and Writing Data

Chapter 6: MapReduce Programming

Chapter 7: Frameworks for Processing Data in Hadoop: YARN and MapReduce

Chapter 8: Pig: Hadoop Programming Made Easier

Chapter 9: Statistical Analysis in Hadoop

Chapter 10: Developing and Scheduling Application Workflows with Oozie

Part III: Hadoop and Structured Data

Chapter 11: Hadoop and the Data Warehouse: Friends or Foes?

Chapter 12: Extremely Big Tables: Storing Data in HBase

Chapter 13: Applying Structure to Hadoop Data with Hive

Chapter 14: Integrating Hadoop with Relational Databases Using Sqoop

Chapter 15: The Holy Grail: Native SQL Access to Hadoop Data

Part IV: Administering and Configuring Hadoop

Chapter 16: Deploying Hadoop

Chapter 17: Administering Your Hadoop Cluster

Part V: The Part of Tens

Chapter 18: Ten Hadoop Resources Worthy of a Bookmark

Chapter 19: Ten Reasons to Adopt Hadoop

Index About the Author
Roman B. Melnyk is a senior member of the DB2 Information Development team. Paul Zikopoulos is the executive for Technical Sales in IBM Information Management

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