Difference between revisions of "Hadoop Hands-on"
From Gridkaschool
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=Prerequisites= |
=Prerequisites= |
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* Basic understanding of Unix/Linux OS management is needed to do the exercises. |
* Basic understanding of Unix/Linux OS management is needed to do the exercises. |
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* No prior knowledge of Hadoop is required, as we go through the basic concepts. |
* No prior knowledge of Hadoop is required, as we go through the basic concepts. |
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* For this workshop a personal notebook is recommendet. |
* For this workshop a personal notebook is recommendet. |
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* If you use Windows: please install "PuTTY" and the VMWare-Player. |
* If you use Windows: please install "PuTTY" and the VMWare-Player. |
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=Recommendet Material= |
=Recommendet Material= |
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==Books== |
==Books== |
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| − | * Hadoop the Defenitive Guide [ |
+ | * Hadoop the Defenitive Guide [http://www.amazon.de/Hadoop-Definitive-Guide-Tom-White/dp/1449311520/ref=sr_1_fkmr1_1?ie=UTF8&qid=1345918087&sr=8-1-fkmr1] |
* Hadoop in Action |
* Hadoop in Action |
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* Data Intensive Text Processing with MapReduce |
* Data Intensive Text Processing with MapReduce |
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Revision as of 20:10, 25 August 2012
Tuesday, 28.8.2012, 13:00 - 18:30
Contents
Prerequisites
- Basic understanding of Unix/Linux OS management is needed to do the exercises.
- No prior knowledge of Hadoop is required, as we go through the basic concepts.
- For this workshop a personal notebook is recommendet.
- If you use Windows: please install "PuTTY" and the VMWare-Player.
Recommendet Material
Books
- Hadoop the Defenitive Guide [1]
- Hadoop in Action
- Data Intensive Text Processing with MapReduce
Content
Session A
- The hadoop ecosystem: HDFS, MR, HUE, Sqoop, Hive, Pig, HBase, Flume, Oozie
- What is CDH and the Cloudera-Manager?
- Installation, starting and basic configurations of a small cluster
Session B
- HDFS intro (Name Node, Data Node, Secondary Name Node)
- How is data stored in HDFS?
- Properties and configurations, relevant for efficient working with HDFS.
- HDFS commands
Session C
- Working with the webbased-GUI
- Running and tracking jobs
- Java-API and samples
- Streaming API sample
Session D
- Map Reduce details, Java-API and Streaming (awk sample)
- HDFS details, using the webbased-GUI for deeper insights
- Breaking down a cluster and heal it
Session E
- Intro to Hive and Sqoop
- Dataimport via Sqoop
- Hive scripts
Session F (optional)
- Serialisation and deserialisation (SerDe) and user defined functions (UDF) with Hive
- Workflows with oozie
