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210123 ||| eng |
| 050 |
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4 |
|a QA76.9.D5
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| 100 |
1 |
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|a Eadline, Doug
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| 245 |
0 |
0 |
|a Hadoop fundamentals 2/e
|c Douglas Eadline
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| 246 |
3 |
1 |
|a Hadoop fundamentals livelessons (video training), 2/e
|
| 260 |
|
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|a [Place of publication not identified]
|b Addison-Wesley
|c 2015
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| 300 |
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|a 1 streaming video file (9 hr., 26 min., 48 sec.)
|b digital, sound, color
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| 653 |
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|a Data Mining
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| 653 |
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|a Traitement réparti
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| 653 |
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|a Big data / http://id.loc.gov/authorities/subjects/sh2012003227
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| 653 |
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|a Electronic data processing / Distributed processing / fast / (OCoLC)fst00906987
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| 653 |
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|a Apache Hadoop / fast / (OCoLC)fst01911570
|
| 653 |
|
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|a Données volumineuses
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| 653 |
|
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|a File organization (Computer science) / fast / (OCoLC)fst00924147
|
| 653 |
|
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|a Data mining / fast / (OCoLC)fst00887946
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| 653 |
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|a Electronic data processing / Distributed processing / http://id.loc.gov/authorities/subjects/sh85042293
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| 653 |
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|a File organization (Computer science) / http://id.loc.gov/authorities/subjects/sh85048195
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| 653 |
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|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
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| 653 |
|
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|a Big data / fast / (OCoLC)fst01892965
|
| 653 |
|
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|a Fichiers (Informatique) / Organisation
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| 653 |
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|a Apache Hadoop / http://id.loc.gov/authorities/names/n2013024279
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| 653 |
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|a Exploration de données (Informatique)
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
|
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|b OREILLY
|a O'Reilly
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| 490 |
0 |
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|a Livelessons
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| 500 |
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|a Title and publication information from title screen (viewed November 18, 2014)
|
| 856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/9780134052489/?ar
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 500
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| 082 |
0 |
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|a 000
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| 082 |
0 |
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|a 300
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| 520 |
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|a "Apache Hadoop is a freely available open source tool-set that enables big data analysis. This Hadoop Fundamentals LiveLessons tutorial demonstrates the core components of Hadoop including Hadoop Distriuted File Systems (HDFS) and MapReduce. In addition, the tutorial demonstrates how to use Hadoop at several levels including the native Java interface, C++ pipes, and the universal streaming program interface. Examples of how to use high level tools include the Pig scripting language and the Hive 'SQL like' interface. Finally, the steps for installing Hadoop on a desktop virtual machine, in a Cloud environment, and on a local stand-alone cluster are presented. Topics covered in this tutorial apply to Hadoop version 2 (i.e., MR2 or Yarn)."--Resource description page
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