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project-451.html
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<!DOCTYPE html>
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<meta name="description" content="Course homepage for CS 451/651 Data-Intensive Distributed Computing (Winter 2019) at the University of Waterloo">
<meta name="author" content="Adam Roeigest">
<title>Data-Intensive Distributed Computing</title>
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<div style="float: right"><img width="250" src="images/waterloo_logo.png" alt="University of Waterloo logo"/></div>
<h1>Assignments <br/><small>Data-Intensive Distributed Computing (Fall 2018)</small></h1>
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<li><a href="assignment0-451.html">0</a></li>
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<h3>Final Project</h3>
<p>The final project is a requirement only for graduate students taking CS 651.</p>
<p>The topic of the final project can be on anything you wish in the
space of big data. Anything reasonably related to topics that we
covered in the course is within scope. For reference, there are three
types of projects you might consider:</p>
<ul>
<li>Implement a big data algorithm in MapReduce or Spark: choose a
particular big data algorithm (for processing text, graphs,
relational data, etc.) and implement it. Ideally, the implementation
does not already exist in a library or open-source package. Since we
want you to implement the algorithm from scratch, it might perhaps
be too tempting to simply copy existing
code—see <a href="organization.html">notes on academic
integrity</a>.</li>
<li>Learn and explore a (new) big data processing framework:
although we discussed a variety of processing frameworks in class,
the assignments focused on MapReduce and Spark. Here's your chance
to learn a new processing framework, e.g., Spark Streaming, GraphX,
Giraph, Flink, etc. The project would involve learning to use the
processing framework and doing something interesting with it. The
"something interesting" might be a data mining algorithm, although
note that the expectations would be lower than building something in
MapReduce or Spark, since learning the new framework would form an
essential component of the project.</li>
<li>Perform some interesting data science. Is there a particular
dataset you'd like to explore or analyze? Your project could involve
performing interesting analytics on a dataset—here, the focus
would be the analytical product and the insights gleaned, as opposed
to the raw algorithms themselves. However, a superficial analysis
with existing machine-learning libraries is not enough.</li>
</ul>
<p>You may work in groups of up to three, or you can also work by
yourself if you wish. The amount of effort devoted to the project
should be proportional to the number of people in the team. As a
guideline, the level of effort should be comparable to two assignments
per person.</p>
<p>When you are ready, send me <code>([email protected] )</code> an
email describing what you'd like to work on. I will provide you with
feedback on appropriateness and scope of your proposed project. The
"soft" deadline for this proposal is March 15, 2019. There is no
penalty if you miss this deadline, but it is in your best interest to
not leave this proposal to the last minute.</p>
<p>The deliverable for the final project is a report. Use
the <a href="http://www.acm.org/publications/proceedings-template">ACM
Templates</a>. The contents of the report will vary depending on the
type of project you are doing. However, it should certainly describe
the goal of you project (what is your learning objective, or what
problem are you trying to solve), your methodology, and some kind of
evaluation of your results or progress. There are no hard limits on
the length of your final report, but you should target something in
the range of 5-10 pages.
<p>The (hard) deadline for submission of your project report is 1pm on
April 19, 2018.</p>
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