Difference between revisions of "Hadoop Workshop"

From Gridkaschool
(Content)
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== Important Information ==
 
== Important Information ==
   
* For this workshop a personal notebook is necessary. You will use [VirtualBox] to run the WorkshopVW
+
* For this workshop a personal notebook is necessary.
  +
* You will use [VirtualBox] to run the Workshop-VM.
* If you use Windows, please prepare the program "PuTTY" for this workshop:
 
  +
* Please download the VM here ... ('''TODO''': ''ask Pavel for the download location'')
http://the.earth.li/~sgtatham/putty/latest/x86/putty.exe
 
   
 
== Abstract ==
 
== Abstract ==

Revision as of 18:52, 18 August 2014

Content

  • Session 1 - Setup
    • The Hadoop Ecosystem
      • Prepare the DEMO VM (we use a prepared virtual cluster in pseudo-distributed mode)
      • Working with HUE, the Hadoop Web-UI
  • Session 2 - The Kite-SDK, a Convinient Framework
    • The KITE-SDK
      • Accessing datasets using the KITE-API
      • Metadata management
      • Kite-Modules
  • Session 3 - Real Time Indexing
    • How to index large datasets with Cloudera Search?
      • Importing data with Flume
      • Real Time Indexing with Morphlines
  • Session 4 - Introduction to Apache Crunch
    • Data processing pipelines for Spark, MapReduce, or simply a Workstation
      • The Crunch data model
      • Crunch data pipelines

Material

Slides:

 will be available after the workshop

Hand-Out:

 will be provided as a hardcopy and as PDF after the workshop


Important Information

  • For this workshop a personal notebook is necessary.
  • You will use [VirtualBox] to run the Workshop-VM.
  • Please download the VM here ... (TODO: ask Pavel for the download location)

Abstract

In the last couple of years cloud computing has achieved an important status in the IT scene.
The renting of computing power, storage and applications according to requirements is regarded as future business.
This tutorial course gives an introduction of the basic concepts of the Infrastructure-as-a-Service (IaaS) model
based on the cloud offerings provided by Amazon, one of the present leading commercial cloud computing providers.

Workshop Exercise

Efficient Data Management with Apache Hadoop We will walk through the dataset life cycle. Starting with data ingestion and real time indexing we use several tools to conserve important datasets and to extract information using high level processing and query frameworks.

Tools

  • HUE
  • Flume
  • SOLR
    • Hive & Impala
    • Crunch & MapReduce