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Distributed Systems
Distributed Systems
One of the most important recent developments in computing is the growth in distributed and parallel applications.TutorialsContributed course contentHadoop tools and resourcesVideo lectures
Tutorials
In these tutorials, we distinguish between local programming (on a single machine) and distributed programming using multiple components via a network.
We cover what designers and programmers need to consider in developing applications in a distributed environment. We also cover parallel computation using an open source tool called Hadoop, which is a MapReduce implementation, running on a distributed file system. The goal is to help build an understanding of these important new trends, and provide opportunities to practice with them.
Intro to DesignIntro to Parallel Programming and MapReduce
Contributed Course Content
These submissions from industry and academia are designed to help teach distributed computing to students around the world.

Cluster Computing and MapReduce Mini Lecture Series
By Aaron Kimball, Sierra Michels-Slettvet, Christophe Bisciglia
Summer 2007
During the Summer of 2007 a week long course in Cluster Computing and MapReduce was offered to interns working at Google. This submission contains the materials used in that class, along with video recordings of each of the lectures. This material builds on Introduction to Problem Solving on Large Scale Clusters, listed below.

Introduction to Problem Solving on Large Scale Clusters
By Aaron Kimball, Sierra Michels-Slettvet, Christophe Bisciglia, et al.
Spring 2007
The University of Washington ran an upper-division course on Distributed Computing with MapReduce in Spring 2007. This submission contains the materials used for the class: five lectures in Powerpoint format, as well as four lab exercises designed to create a toolbox of distributed algorithms and data structures for the student. These were completed by students in the course on a cluster running Hadoop. This material builds on MapReduce in a Week, listed below.
Lectures -Labs

MapReduce in a Week
By Hannah Tang, Albert Wong, Aaron Kimball
Winter 2007
This submission contains a complete set of lectures, programming assignments, and reading materials. It is designed to provide you with all the material you need in order to teach MapReduce as a section within a course on distributed systems.
Lectures -Exercises
Hadoop tools and resources
Getting started with a distributed system environment can be challenging. To help with this, we've assembled a few tools and resources that can be useful to both students and educators.
Hadoop Virtual Image
by Google
This VMware image contains a preconfigured single node instance of Hadoop. This provides the same interface as a full cluster without any of the overhead. It is suitable for educators exploring the platform and students working independently. The following Download and VMware Player links point to websites external to Google.
Documentation -Download (110.1 Mb)-VMware Player
MapReduce Tools for Eclipse Plug-In
by IBM
A robust plug-in that brings Hadoop support to the Eclipse platform. Features include server configuration, support for launching MapReduce jobs and browsing the distributed file system. The following Plug-in and Eclipse links point to websites external to Google.
Plug-in-Eclipse
Sample Datasets
The following links provide interesting data samples that are most efficiently manipulated using distributed systems techniques.
Wikipedia-Netflix Prize
Video lectures
In this area, you will find a set of video-taped lectures from Google Video on various technology areas. These videos are great opportunities for students and faculty to hear directly from some of the current pioneers in high-tech. They can also potentially serve as "guest lectures" for courses in these areas.
Building Large Systems at Google, Shiva ShivakumarBig Table: A Distributed Structured Storage System, Jeff DeanTesting Distributed Systems, MartinOmander, Jason Huggins
Building Large Systems at Google
Presenter: Shiva Shivakumar - Google Distinguished Entreprenuer
Google deals with large amounts of data and millions of users. We'll take a behind-the-scenes look at some of the distributed systems and computing platform that power Google's various products, and make the products scalable and reliable.
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Big Table: A Distributed Structured Storage System
Presenter: Jeff Dean - Google Distinguished Engineer
Google's Jeff Dean discusses the Bigtable content storage system used in google's backend at the University of Washington.
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Testing Distributed Systems
Prsenters: Martin Omander, Jason Huggins
Testing Distributed Systems with AJAX, XML - Lessons Learned from Google Checkout.
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