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<!DOCTYPE html>
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<meta name="description" content="Course homepage for CS 489 Big Data Infrastructure (Winter 2017) at the University of Waterloo">
<meta name="author" content="Jimmy Lin">
<title>Big Data Infrastructure</title>
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<div style="float: right"/><img src="images/waterloo_logo.png"/></div>
<h1>Syllabus <small>CS 489/698 Big Data Infrastructure (Winter 2017)</small></h1>
</div>
<section id="schedule">
<div>
<h3>Schedule of Classes</h3>
<table class="table table-striped table-condensed">
<thead>
<tr><td><b>Week</b></td>
<td><b>Date</b></td>
<td><b>Topic</b></td>
<td><b>Assignment Due</b></td></tr>
</thead>
<tbody>
<tr><td>1</td><td>Jan 3/Jan 5</td><td><a href="#week1">Introduction</a></td><td></td></tr>
<tr><td>2</td><td>Jan 10/Jan 12</td><td><a href="#week2">MapReduce Algorithm Design</a></td><td><a href="assignment0.html">Assignment #0: Warmup</a> (Jan 12)</td></tr>
<tr><td>3</td><td>Jan 17/Jan 19</td><td><a href="#week3">From MapReduce to Spark</a></td><td><a href="assignment1.html">Assignment #1: Counting in MapReduce</a> (Jan 19)</td></tr>
<tr><td>4</td><td>Jan 24/Jan 26</td><td><a href="#week4">Analyzing Text</a></td><td><a href="assignment2.html">Assignment #2: Counting in Spark</a> (Jan 26)</td></tr>
<tr><td>5</td><td>Jan 31/Feb 2</td><td><a href="#week5">Analyzing Graphs</a></td><td><a href="assignment3.html">Assignment #3: Inverted Indexing</a> (Feb 2)</td></tr>
<tr><td>6</td><td>Feb 7/Feb 9</td><td><a href="#week6">Analyzing Relational Data I</a></td><td><a href="assignment4.html">Assignment #4: Multi-Source Personalized PageRank</a> (Feb 9)</td></tr>
<tr><td>7</td><td>Feb 14</td><td><a href="#week7">Analyzing Relational Data II</a></td><td></td></tr>
<tr><td colspan="4">No classes!</td></tr>
<tr><td>8</td><td>Feb 28/Mar 2</td><td><a href="#week8">Data Mining I</a></td><td><a href="assignment5.html">Assignment #5: Data Warehousing</a></td></tr>
<tr><td>9</td><td>Mar 7/Mar 9</td><td><a href="#week9">Data Mining II</a></td><td></td></tr>
<tr><td>10</td><td>Mar 14/Mar 16</td><td><a href="#week10">Mutable State</a></td><td>Assignment #6: TBA</td></tr>
<tr><td>11</td><td>Mar 21/Mar 23</td><td><a href="#week11">Analyzing Graphs, Redux</a></td><td></tr>
<tr><td>12</td><td>Mar 28/Mar 30</td><td><a href="#week12">Real-Time Data Analytics</a></td><td>Assignment #7: TBA</td></tr>
</tbody>
</table>
</div>
</section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week1" style="padding-top:35px"><div>
<h3>Week 1: Introduction <small>January 3/5</small></h3>
<h4>Topics</h4>
<ul>
<li>What's this course about?</li>
<li>Why big data?</li>
<li>The datacenter is the computer and other "big ideas"</li>
<li>The MapReduce programming model</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Readings</h4>
<ul>
<li><a href="http://lintool.github.com/MapReduceAlgorithms/ed1n/MapReduce-algorithms.pdf">Data-Intensive Text Processing with MapReduce</a>
<ul>
<li>Chapter 1: Introduction</li>
<li>Chapter 2: MapReduce Basics</li>
</ul>
</li>
<li><i>(Optional, but recommended)</i> Hadoop: The Definitive Guide (4th Edition):
<ul>
<li>Chapter 1: Meet Hadoop</li>
<li>Chapter 2: MapReduce</li>
<li>Chapter 3: The Hadoop Distributed Filesystem (Focus on the mechanics of the HDFS commands and don't worry so much about learning the Java API all at once—you'll pick it up in time.)</li>
</ul>
</ul>
<p style="padding-top: 5px"/>
<h4>Slides</h4>
<p>
<a href="slides/week01a.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week01a.pdf" class="btn btn-sm btn-info" role="button">PDF</a></b> <b>Part 1: January 3</b>
</p>
<p>
<a href="slides/week01b.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week01b.pdf" class="btn btn-sm btn-info" role="button">PDF</a> <b>Part 2: January 5</b>
</p>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week2" style="padding-top:35px"><div>
<h3>Week 2: MapReduce Algorithm Design <small>January 10/12</small></h3>
<h4>Topics</h4>
<ul>
<li>MapReduce physical execution</li>
<li>MapReduce design patterns</li>
<li>Intermediate aggregation and combiners</li>
<li>Partitioning, grouping, sorting, and monoids</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Readings</h4>
<ul>
<li><a href="http://lintool.github.com/MapReduceAlgorithms/ed1n/MapReduce-algorithms.pdf">Data-Intensive Text Processing with MapReduce</a>
<ul>
<li>Chapter 3: MapReduce Algorithm Design</li>
</ul>
</li>
<li><i>(Optional, but recommended)</i> Hadoop: The Definitive Guide (4th Edition):
<ul>
<li>Chapter 5: Hadoop I/O (Read sections "Serialization" and "File-Based Data Structures")</li>
<li>Chapter 6: Developing a MapReduce Application (Skip sections "Setting Up the Development Environment", "Writing a Unit Test with MRUnit" and "MapReduce Workflows")</li>
<li>Chapter 7: How MapReduce Works (Skip section on "Configuration Tuning")</li>
<li>Chapter 8: MapReduce Types and Formats</li>
<li>Chapter 9: MapReduce Features (Read sections on "Counters", "Sorting", and "Side Data distribution")</li>
</ul>
</ul>
<p style="padding-top: 5px"/>
<h4>Slides</h4>
<p>
<a href="slides/week02a.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week02a.pdf" class="btn btn-sm btn-info" role="button">PDF</a></b> <b>Part 1: January 10</b>
</p>
<p>
<a href="slides/week02b.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week02b.pdf" class="btn btn-sm btn-info" role="button">PDF</a> <b>Part 2: January 12</b>
</p>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week3" style="padding-top:35px"><div>
<h3>Week 3: From MapReduce to Spark <small>January 17/19</small></h3>
<h4>Topics</h4>
<ul>
<li>Evolution of dataflow abstractions</li>
<li>MapReduce, Pig, Dryad, Spark, Flink, etc.</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Readings</h4>
<ul>
<li><i>(Optional, but recommended)</i> Learning Spark:
<ul>
<li>Chapter 1: Introduction to Data Analysis with Spark</li>
<li>Chapter 2: Downloading Spark and Getting Started (Skip section on downloading)</li>
<li>Chapter 3: Programming with RDDs</li>
<li>Chapter 4: Working with Key/Value Pairs</li>
<li>Chapter 5: Loading and Saving Your Data (Stop when you get to Structured Data with Spark SQL)</li>
<li>In all the readings above, don't worry about Python and Java since we're only going to be working with Spark's Scala API.</li>
</ul>
</ul>
<p style="padding-top: 5px"/>
<h4>Slides</h4>
<p>
<a href="slides/week03a.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week03a.pdf" class="btn btn-sm btn-info" role="button">PDF</a></b> <b>Part 1: January 17</b>
</p>
<p>
<a href="slides/week03b.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week03b.pdf" class="btn btn-sm btn-info" role="button">PDF</a> <b>Part 2: January 19</b>
</p>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week4" style="padding-top:35px"><div>
<h3>Week 4: Analyzing Text <small>January 24/26</small></h3>
<h4>Topics</h4>
<ul>
<li>Language models and machine translation</li>
<li>Inverted indexing and search</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Readings</h4>
<ul>
<li><a href="http://lintool.github.com/MapReduceAlgorithms/ed1n/MapReduce-algorithms.pdf">Data-Intensive Text Processing with MapReduce</a>
<ul>
<li>Chapter 4: Inverted Indexing for Text Retrieval</li>
</ul>
</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Slides</h4>
<p>
<a href="slides/week04a.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week04a.pdf" class="btn btn-sm btn-info" role="button">PDF</a></b> <b>Part 1: January 24</b>
</p>
<p>
<a href="slides/week04b.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week04b.pdf" class="btn btn-sm btn-info" role="button">PDF</a> <b>Part 2: January 26</b>
</p>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week5" style="padding-top:35px"><div>
<h3>Week 5: Analyzing Graphs <small>January 31/February 2</small></h3>
<h4>Topics</h4>
<ul>
<li>Graph representations</li>
<li>Parallel breadth-first search</li>
<li>PageRank and random walks</li>
<li>Issues and challenges with dataflow abstractions</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Readings</h4>
<ul>
<li><a href="http://lintool.github.com/MapReduceAlgorithms/ed1n/MapReduce-algorithms.pdf">Data-Intensive Text Processing with MapReduce</a>
<ul>
<li>Chapter 5: Graph Algorithms</li>
</ul>
</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Slides</h4>
<p>
<a href="slides/week05a.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week05a.pdf" class="btn btn-sm btn-info" role="button">PDF</a></b> <b>Part 1: January 31</b>
</p>
<p>
<a href="slides/week05b.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week05b.pdf" class="btn btn-sm btn-info" role="button">PDF</a> <b>Part 2: February 2</b>
</p>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week6" style="padding-top:35px"><div>
<h3>Week 6: Analyzing Relational Data I <small>February 7/9</small></h3>
<h4>Topics</h4>
<ul>
<li>OLTP vs. OLAP</li>
<li>Data warehousing and data lakes</li>
<li>ETL</li>
<li>SQL-on-Hadoop</li>
<li>Relational data processing with MapReduce and Spark</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Readings</h4>
<ul>
<li><a href="http://lintool.github.com/MapReduceAlgorithms/ed1n/MapReduce-algorithms.pdf">Data-Intensive Text Processing with MapReduce</a>
<ul>
<li>Chapter 6: Processing Relational Data</li>
</ul>
</li>
<ii><a href="http://homes.cs.washington.edu/~billhowe/mapreduce_a_major_step_backwards.html">MapReduce: A major step backwards</a></li>
<li>Chaudhuri et al. (2011) <a href="http://dl.acm.org/citation.cfm?id=1978562">An overview of business intelligence technology</a>, <i>CACM</i>, 54(8):88-98.</li>
</ul>
<p style="padding-top: 5px"/>
<h4>Slides</h4>
<p>
<a href="slides/week06a.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week06a.pdf" class="btn btn-sm btn-info" role="button">PDF</a></b> <b>Part 1: February 7</b>
</p>
<p>
<a href="slides/week06b.pptx" class="btn btn-sm btn-primary" role="button">PPTX (Mac)</a>
<a href="slides/week06b.pdf" class="btn btn-sm btn-info" role="button">PDF</a></b> <b>Part 2: February 9</b>
</p>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week7" style="padding-top:35px"><div>
<h3>Week 7: Analyzing Relational Data II <small>February 14</small></h3>
<h4>Topics</h4>
<ul>
<li>Optimizations for relational processing</li>
<li>Row vs. column stores</li>
<li>Vectorized processing</li>
<li>Semistructured data and record reconstruction (Parquet)</li>
</ul>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week8" style="padding-top:35px"><div>
<h3>Week 8: Data Mining I <small>February 28/March 2</small></h3>
<h4>Topics</h4>
<ul>
<li>Supervised machine learning: binary classification</li>
<li>Logistic regression, gradient descent, stochastic gradient descent, ensemble methods</li>
<li>Production machine learning pipelines</li>
</ul>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week9" style="padding-top:35px"><div>
<h3>Week 9: Data Mining II <small>March 7/9</small></h3>
<h4>Topics</h4>
<ul>
<li>Hashing: minhash, random projections, etc.</li>
<li>Clustering: <i>k</i>-means, Gaussian mixture models</li>
</ul>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week10" style="padding-top:35px"><div>
<h3>Week 10: Mutable State <small>March 14/16</small></h3>
<h4>Topics</h4>
<ul>
<li>Bigtable/HBase: Log-structure merge trees</li>
<li>Distributed hash tables</li>
<li>Consistency, latency, and availability tradeoffs</li>
</ul>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week11" style="padding-top:35px"><div>
<h3>Week 11: Analyzing Graphs, Redux <small>March 21/23</small></h3>
<h4>Topics</h4>
<ul>
<li>Bulk synchronous parallel: "think like a vertex" (Giraph)</li>
<li>Alternative approaches: GraphX</li>
</ul>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
<!-- ---------------------------------------------------------------------------------------------------- -->
<section id="week12" style="padding-top:35px"><div>
<h3>Week 12: Real-Time Data Analytics <small>March 28/30</small></h3>
<h4>Topics</h4>
<ul>
<li>Stream processing issues and models</li>
<li>Probabilistic data structures (hyerloglog counters, bloom filters, count-min sketches, etc.)</li>
<li>Integrating batch and stream processing</li>
</ul>
<p style="padding-top: 20px"><a href="#">Back to top</a></p>
</div></section>
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