Hadoop For Dummies
Paperback Engels 2014 9781118607558Samenvatting
Let Hadoop For Dummies help harness the power of your data and rein in the information overload
Big data has become big business, and companies and organizations of all sizes are struggling to find ways to retrieve valuable information from their massive data sets with becoming overwhelmed. Enter Hadoop and this easy–to–understand For Dummies guide. Hadoop For Dummies helps readers understand the value of big data, make a business case for using Hadoop, navigate the Hadoop ecosystem, and build and manage Hadoop applications and clusters.
Explains the origins of Hadoop, its economic benefits, and its functionality and practical applications
Helps you find your way around the Hadoop ecosystem, program MapReduce, utilize design patterns, and get your Hadoop cluster up and running quickly and easily
Details how to use Hadoop applications for data mining, web analytics and personalization, large–scale text processing, data science, and problem–solving
Shows you how to improve the value of your Hadoop cluster, maximize your investment in Hadoop, and avoid common pitfalls when building your Hadoop cluster
From programmers challenged with building and maintaining affordable, scaleable data systems to administrators who must deal with huge volumes of information effectively and efficiently, this how–to has something to help you with Hadoop.
Specificaties
Lezersrecensies
Inhoudsopgave
<p>Part I: Getting Started with Hadoop 7</p>
<p>Chapter 1: Introducing Hadoop and Seeing What It s Good For 9</p>
<p>Chapter 2: Common Use Cases for Big Data in Hadoop 23</p>
<p>Chapter 3: Setting Up Your Hadoop Environment 41</p>
<p>Part II: How Hadoop Works 51</p>
<p>Chapter 4: Storing Data in Hadoop: The Hadoop Distributed File System 53</p>
<p>Chapter 5: Reading and Writing Data 69</p>
<p>Chapter 6: MapReduce Programming 83</p>
<p>Chapter 7: Frameworks for Processing Data in Hadoop: YARN and MapReduce 103</p>
<p>Chapter 8: Pig: Hadoop Programming Made Easier 117</p>
<p>Chapter 9: Statistical Analysis in Hadoop 129</p>
<p>Chapter 10: Developing and Scheduling Application Workflows with Oozie 139</p>
<p>Part III: Hadoop and Structured Data 155</p>
<p>Chapter 11: Hadoop and the Data Warehouse: Friends or Foes? 157</p>
<p>Chapter 12: Extremely Big Tables: Storing Data in HBase 179</p>
<p>Chapter 13: Applying Structure to Hadoop Data with Hive 227</p>
<p>Chapter 14: Integrating Hadoop with Relational Databases Using Sqoop 269</p>
<p>Chapter 15: The Holy Grail: Native SQL Access to Hadoop Data 303</p>
<p>Part IV: Administering and Configuring Hadoop 313</p>
<p>Chapter 16: Deploying Hadoop 315</p>
<p>Chapter 17: Administering Your Hadoop Cluster 335</p>
<p>Part V: The Part of Tens 359</p>
<p>Chapter 18: Ten Hadoop Resources Worthy of a Bookmark 361</p>
<p>Chapter 19: Ten Reasons to Adopt Hadoop 371</p>
<p>Index 379</p>
Rubrieken
- advisering
- algemeen management
- coaching en trainen
- communicatie en media
- economie
- financieel management
- inkoop en logistiek
- internet en social media
- it-management / ict
- juridisch
- leiderschap
- marketing
- mens en maatschappij
- non-profit
- ondernemen
- organisatiekunde
- personal finance
- personeelsmanagement
- persoonlijke effectiviteit
- projectmanagement
- psychologie
- reclame en verkoop
- strategisch management
- verandermanagement
- werk en loopbaan