PLURALSIGHT_DATA_SCIENCE_AND_HADOOP_WORKFLOWS_AT_SCALE_WITH_SCALDING_TUTORIAL-kEISO

Section

Appz

Group

kEISO

Size

1,13 GB

Files

27

Date

2015-03-01

NFO

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  ▀▓████▀▓█▀ ▀▓▀                                               ▀▓  ▀█▓▀████▓▀
 █ ▀█▓▓██▄▄██    TITLE: DATA SCIENCE & HADOOP WORKFLOWS AT SCALE  ██▄▄██▓▓█▀ █
 █▀ ▐█▒▓██░██           WITH SCALDING                             ██░██▓▒█▌ ▀█
 █▀  █▓███▒█▌                                                     ▐█▒███▓█  ▀█
 █▀ ▐█▓███▓█░                                                     ░█▓███▓█▌ ▀█
 █▀ ▐██████▌     PUBLISHER..........: PLURALSIGHT                  ▐██████▌ ▀█
 █▀ ▀▀████▓      LINK...............: http://is.gd/AyQQyx           ▓████▀▀ ▀█
 ▌ ▓██▌▄ ▀▀      AUTHOR.............: AHMAD ALKILANI                ▀▀ ▄▐██▓ ▐
 ▌▐███░▒███▌     LEVEL..............: BEGINNER                     ▐███▒░███▌▐
 ▌ ████▓████     RUNTIME............: 02H08M                       ████▓████ ▐
 █ ▐▓█▀█████░    LANGUAGE...........: ENGLISH                     ░█████▀█▓▌ █
 █▀ ▀▄█▄▄▀▀█▓    RELEASE TYPE.......: RETAIL                      ▓█▀▀▄▄█▄▀ ▀█
 █▀▄ ▄▀███▓▄     RELEASE FORMAT.....: ISO                          ▄▓███▀▄ ▄▀█
 █▀█ ▐▓▄▀████    STORE DATE:........: 2014.12.04                  ████▀▄▓▌ █▀█
 █▀█ ▐█▌▓██▓     RELEASE DATE.......: 2015.03.01                   ▓██▓▐█▌ █▀█
 ▓▀█ ▓▌░██▓      ISO SIZE...........: 1.249.597.440 B               ▓██░▐▓ █▀▓
 ▒▀█ █ ▓█▓       ISO CHECKSUM.......: DFE3976F                       ▓█▓ █ █▀▒
 ░ █ ▌░██        DISKCOUNT..........: 25 X 50MB                       ██░▐ █ ░
   ▓█▌▓█▌        SAVED MONEY........: YOU DID!                          ▐█▓▐█▓
 ░ ▒█▐██         DISKNAME...........: keiso_psdshwatsws                ██▌█▒ ░
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█▀  ▓░  ▄ █▄▌██ ▄ ▀ ▀█▌▐▓▀         TUTORIAL          ▀▓▌▐█▀ ▀ ▄ ██▐▄█ ▄  ░▓  ▀█
 ▄▀ ▄ ▀▄   ▀▌▓█   ▀▄▄ ▀ ▀▄                           ▄▀ ▀ ▄▄▀   █▓▐▀   ▄▀ ▄ ▀▄
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 █▀█ ▄▓  ▄ ▐▌                                                     ▐▌ ▄  ▓▄ █▀█
 █▀█ ▒░  ░  This course teaches you how to use Scalding (a domain    ░  ░▒ █▀█
 ▓▀█ ▒░  specific language) built on Scala and Cascading to build       ░▒ █▀▓
 ▒▀█ ░▓  distributed applications on Hadoop. The course also focuses    ▓░ █▀▒
 ░ █  ▒  on the data science aspect using Algebird, an abstract         ▒  █ ░
   ▓  ░  algebra library for Scala, to solve real-world                 ░  ▓
 ░ ▒  ░  sketching/streaming problems on distributed systems. You       ░  ▒ ░
   ░     will learn how to reason about a variety of problems, how      ░
   ░     to build and test locally, and how to deploy on Hadoop. You    ░
   ░     will also learn the algorithms used to solve problems at       ░
   ░     scale where performance, compute and memory resources, and     ░
   ░     the window of time you have to process streaming data are      ░
   ░     all challenges you'll have to overcome, and how you can use    ░
   ░     Scalding and Algebird to solve for these constraints. This     ░
   ░     course also covers some Scala basics to get you up to speed    ░
   ░     and looks into how you can monitor, visualize, and             ░
   ░     troubleshoot your application's workflow and performance       ░
   ░     problems. Watch this course if you were considering, or        ░
   ░     already know how to use Pig, Hive, or any other DSL for        ░
   ░     Hadoop and not only wanted more power over your workflows,     ░
   ░     but also a DSL that is actively being developed to support     ░
   ░     up and coming execution frameworks like Apache Tez and         ░
   ░     Apache Spark with all the flexibility that a full              ░
   ░     functional programming language like Scala has to offer. If    ░
   ░     you're serious about learning how to build enterprise-grade    ░
   ░     applications on Hadoop, data science, and Lambda               ░
   ░     architectures, then this course is for you.                    ░
 ░                                                                           ░
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█▀  ▓░  ▄ █▄▌██ ▄ ▀ ▀█▌▐▓▀       NOTES / NEWS        ▀▓▌▐█▀ ▀ ▄ ██▐▄█ ▄  ░▓  ▀█
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 ▌██  ░                            SHOUTOUTS                            ░  ██▐
 ▌▐▓█                                                                     █▓▌▐
 ▌ ░▓█                                                                   █▓░ ▐
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