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<h1 class="title toc-ignore">Distributed learning</h1>
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<div id="cm013---may-7-2018" class="section level1">
<h1>cm013 - May 7, 2018</h1>
<div id="overview" class="section level2">
<h2>Overview</h2>
<ul>
<li>Discuss the need for distributed computing</li>
<li>Illustrate the split-apply-combine analytical pattern</li>
<li>Define parallel processing</li>
<li>Define SQL</li>
<li>Demonstrate how to access local and remote SQL databases</li>
<li>Introduce Hadoop and Spark as distributed computing platforms</li>
<li>Introduce the <code>sparklyr</code> package</li>
<li>Demonstrate how to use <code>sparklyr</code> for machine learning using the Titanic data set</li>
</ul>
</div>
<div id="before-class" class="section level2">
<h2>Before class</h2>
<ul>
<li><p>Install <code>sparklyr</code> and H2O on your local computer. Run the code below to install all necessary packages and set the correct options.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">install.packages</span>(<span class="kw">c</span>(<span class="st">"sparklyr"</span>, <span class="st">"rsparkling"</span>))
<span class="kw">options</span>(<span class="dt">rsparkling.sparklingwater.version =</span> <span class="st">"2.1.0"</span>)
<span class="kw">library</span>(sparklyr)
<span class="kw">spark_install</span>(<span class="dt">version =</span> <span class="st">"2.1.0"</span>)</code></pre></div>
<p>Last year, 70% of students were able to successfully install these packages without problems. The others ran into problems. Make sure to attempt installing these packages before class so if you have errors we can debug them before you need to use the packages.</p></li>
</ul>
</div>
<div id="slides-and-links" class="section level2">
<h2>Slides and links</h2>
<ul>
<li><a href="extras/cm013_slides.html">Slides</a></li>
<li><a href="distrib001_database.html">Accessing databases using <code>dbplyr</code></a></li>
<li><a href="distrib002_sac.html">Split-apply-combine and parallel computing</a></li>
<li><p><a href="distrib003_spark.html">Spark and <code>sparklyr</code></a></p></li>
<li><a href="http://www.jstatsoft.org/v40/i01/paper">The split-apply-combine strategy for data analysis</a> - paper by Hadley Wickham establishing a general overview of split-apply-combine problems. Note that the <code>plyr</code> package is now deprecated in favor of <code>dplyr</code> and the other <code>tidyverse</code> packages</li>
<li><a href="https://cran.r-project.org/web/packages/dplyr/vignettes/databases.html">Accessing databases using <code>dplyr</code></a></li>
<li><a href="https://cloud.google.com/bigquery/public-data/nyc-tlc-trips">Taxi dataset</a></li>
<li><a href="https://github.com/rstats-db/bigrquery"><code>bigrquery</code></a> - instructions for setting up an account to access Google Bigquery databases</li>
<li><p><a href="http://spark.rstudio.com/"><code>sparklyr</code></a> - introduction to the <code>sparklyr</code> interface for Spark</p></li>
</ul>
</div>
<div id="what-you-need-to-do" class="section level2">
<h2>What you need to do</h2>
</div>
</div>
<p>This work is licensed under the <a href="http://creativecommons.org/licenses/by-nc/4.0/">CC BY-NC 4.0 Creative Commons License</a>.</p>
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