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YouTube Page Rank Graph Data Analytics .htm
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YouTube Page Rank Graph Data Analytics .htm
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<div class=WordSection1>
<p class=MsoTocHeading>By Afsar Ali</p>
<p class=MsoToc1><span class=MsoHyperlink><a href="#_Toc525334867"><b>YouTube
Page Rank Graph Data Analytics</b><span style='display:none;text-decoration:
none'>. </span><span
style='display:none;text-decoration:none'>1</span></a></span></p>
<p class=MsoToc2><span class=MsoHyperlink><a href="#_Toc525334868">(1) Answer
questions about PageRank:<span style='display:none;text-decoration:none'> </span><span style='display:none;text-decoration:none'>1</span></a></span></p>
<p class=MsoToc3><span class=MsoHyperlink><a href="#_Toc525334869">1.<span
style='text-decoration:none'> </span>Discuss the YouTube dataset used in
this use case<span style='display:none;text-decoration:none'> </span><span style='display:none;text-decoration:none'>1</span></a></span></p>
<p class=MsoToc3><span class=MsoHyperlink><a href="#_Toc525334870">2.<span
style='text-decoration:none'> </span>Describe the PageRank<span
style='display:none;text-decoration:none'>. </span><span
style='display:none;text-decoration:none'>1</span></a></span></p>
<p class=MsoToc3><span class=MsoHyperlink><a href="#_Toc525334871">3.<span
style='text-decoration:none'> </span>Describe each step from 1 - 10 in your
own words<span style='display:none;text-decoration:none'> </span><span style='display:none;text-decoration:none'>1</span></a></span></p>
<p class=MsoToc3><span class=MsoHyperlink><a href="#_Toc525334872">4.<span
style='text-decoration:none'> </span>What did you run about Graph Processing
in this use case?<span style='display:none;text-decoration:none'>. </span><span style='display:none;text-decoration:none'>1</span></a></span></p>
<p class=MsoToc2><span class=MsoHyperlink><a href="#_Toc525334873">(2) Paste
the screen shot of your Jupyter Notebook of yours.<span style='display:none;
text-decoration:none'> </span><span
style='display:none;text-decoration:none'>1</span></a></span></p>
<p class=MsoNormal> </p>
<h1><a name="_Toc525334867"><b><span style='font-size:14.0pt'>YouTube Page Rank
Graph Data Analytics</span></b></a> </h1>
<p class=MsoNormal style='margin-bottom:0in;margin-bottom:.0001pt;line-height:
normal'> </p>
<h2><a name="_Toc525334868">(1) Answer questions about PageRank:</a></h2>
<h3 style='margin-left:.5in;text-indent:-.25in'><a name="_Toc525334869">1.<span
style='font:7.0pt "Times New Roman"'> </span>Discuss the YouTube
dataset used in this use case</a></h3>
<p class=MsoListParagraphCxSpFirst style='margin-top:0in;margin-right:0in;
margin-bottom:0in;margin-left:1.0in;margin-bottom:.0001pt;line-height:normal'>YouTube
online social network dataset includes the communities which are basically user
defined groups that other users can join in. Such user-defined groups are
called ground-truth communities We are using this data set figure out
clusters of communities in YouTube groups. </p>
<p class=MsoListParagraphCxSpLast style='margin-top:0in;margin-right:0in;
margin-bottom:0in;margin-left:1.0in;margin-bottom:.0001pt;line-height:normal'> </p>
<h3 style='margin-left:.5in;text-indent:-.25in'><a name="_Toc525334870">2.<span
style='font:7.0pt "Times New Roman"'> </span>Describe the PageRank</a></h3>
<p class=MsoListParagraphCxSpFirst style='margin-top:0in;margin-right:0in;
margin-bottom:0in;margin-left:1.0in;margin-bottom:.0001pt;line-height:normal'>PageRank
is used to determine the relative importance of an object inside a graph data
set. Its algorithm measures the how important of each node in a graph, assuming
an edge from another node to this node represents an endorsement. Page Rank was
used by Google Search to rank websites in their search engine results. PageRank
was named after Larry Page, one of the founders of Google. For example, It is a
way of measuring the importance of website or influence of social network, the
user is considered higher influence in the network because follower quantity. GraphX
provides two implementations of PageRank: Static and Dynamic. Static PageRank
runs for a fixed number of iterations to generate PageRank values for a given
set of nodes in a graph data set. while Dynamic PageRank until PageRank values
converge based on a predefined tolerance value.</p>
<p class=MsoListParagraphCxSpLast style='margin-top:0in;margin-right:0in;
margin-bottom:0in;margin-left:1.0in;margin-bottom:.0001pt;line-height:normal'> </p>
<h3 style='margin-left:.5in;text-indent:-.25in'><a name="_Toc525334871">3.<span
style='font:7.0pt "Times New Roman"'> </span>Describe each
step from 1 - 10 in your own words</a></h3>
<p class=MsoListParagraphCxSpFirst style='margin-top:0in;margin-right:0in;
margin-bottom:0in;margin-left:1.0in;margin-bottom:.0001pt;text-indent:-.25in;
line-height:normal'>1.<span style='font:7.0pt "Times New Roman"'>
</span>First we imported all the necessary tools such as spark, graphx, RDD,
Then we Load the edges or relationships of the data, compute the details like
edges, vertices or notes, look at the counts of our vertices or notes, looked
at the count of our edges or relationships.</p>
<p class=MsoListParagraphCxSpMiddle style='margin-top:0in;margin-right:0in;
margin-bottom:0in;margin-left:1.0in;margin-bottom:.0001pt;text-indent:-.25in;
line-height:normal'>2.<span style='font:7.0pt "Times New Roman"'>
</span>Next step is to see the Triangle count since we are using you tube
community data set, thus detection of number of triangles passing through each
vertex. Basically to count our clusters </p>
<p class=MsoListParagraphCxSpMiddle style='margin-top:0in;margin-right:0in;
margin-bottom:0in;margin-left:1.0in;margin-bottom:.0001pt;text-indent:-.25in;
line-height:normal'>3.<span style='font:7.0pt "Times New Roman"'>
</span>The we calculate the Graph Degrees basically the number of head ends
adjacent to a vertex (indegree) and the number of tail ends adjacent to a
vertex (outdegree). And the amount of connections the nodes or vertices has. </p>
<p class=MsoListParagraphCxSpLast style='margin-top:0in;margin-right:0in;
margin-bottom:0in;margin-left:1.0in;margin-bottom:.0001pt;text-indent:-.25in;
line-height:normal'>4.<span style='font:7.0pt "Times New Roman"'>
</span>I couldnt go past step 9 after attempting multiple times. But this step
would show the fixed # of Static page rank and step 10 would show the top 5
Static Page Rank</p>
<p class=MsoNormal style='margin-bottom:0in;margin-bottom:.0001pt;line-height:
normal'> </p>
<h3 style='margin-left:.5in;text-indent:-.25in'><a name="_Toc525334872">4.<span
style='font:7.0pt "Times New Roman"'> </span>What did you run
about Graph Processing in this use case?</a></h3>
<p class=MsoListParagraph style='margin-top:0in;margin-right:0in;margin-bottom:
0in;margin-left:1.0in;margin-bottom:.0001pt;line-height:normal'>Due to Graph
Processing we had an insight using graph data statistics which showed relations
and ranked those relationships by popularity. This is really cool especially as
there are increasing growth of connected data due to social media and big data,
it would be great for predictive analytics and recommendation engine and insights
into something that would feel unorganized. I love how using cluster or
connected components we can see how a bigger and smaller clusters are
organized. </p>
<p class=MsoNormal style='margin-bottom:0in;margin-bottom:.0001pt;line-height:
normal'> </p>
<h2><a name="_Toc525334873">(2) Paste the screen shot of your Jupyter Notebook
of yours.</a></h2>
<p class=MsoNormal style='margin-bottom:0in;margin-bottom:.0001pt;line-height:
normal'><img width=721 height=420 id="Picture 1"
src="YouTube%20Page%20Rank%20Graph%20Data%20Analytics%20_files/image001.jpg"></p>
<p class=MsoNormal style='margin-bottom:0in;margin-bottom:.0001pt;line-height:
normal'><span style='font-size:10.0pt'> </span></p>
<p class=MsoNormal align=center style='margin-bottom:0in;margin-bottom:.0001pt;
text-align:center;line-height:normal'><span style='font-size:10.0pt'> </span></p>
<p class=MsoNormal style='margin-bottom:0in;margin-bottom:.0001pt;line-height:
normal'><img width=432 height=459 id="Picture 2"
src="YouTube%20Page%20Rank%20Graph%20Data%20Analytics%20_files/image002.jpg"></p>
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