Author: matei
Date: Thu Oct 10 04:50:39 2013
New Revision: 1530857
URL: http://svn.apache.org/r1530857
Log:
Update research paper links
Modified:
incubator/spark/research.md
incubator/spark/site/research.html
Modified: incubator/spark/research.md
URL:
http://svn.apache.org/viewvc/incubator/spark/research.md?rev=1530857&r1=1530856&r2=1530857&view=diff
==============================================================================
--- incubator/spark/research.md (original)
+++ incubator/spark/research.md Thu Oct 10 04:50:39 2013
@@ -9,7 +9,7 @@ navigation:
<h2>Spark Research</h2>
<p>
-Spark started as a research project at UC Berkeley in the <a
href="https://amplab.cs.berkeley.edu";>AMPLab</a>, which focuses on big data
analytics.
+Apache Spark started as a research project at UC Berkeley in the <a
href="https://amplab.cs.berkeley.edu";>AMPLab</a>, which focuses on big data
analytics.
</p>
<p class="noskip">
@@ -19,7 +19,7 @@ Our goal was to design a programming mod
<ul>
<li><em>Iterative algorithms</em>, including many machine learning
algorithms and graph algorithms like PageRank.</li>
<li><em>Interactive data mining</em>, where a user would like to load data
into RAM across a cluster and query it repeatedly.</li>
- <li><em>OLAP reports</em> that run multiple aggregation queries on the same
data.</li>
+ <li><em>Streaming applications</em> that maintain aggregate state over
time.</li>
</ul>
<p>
@@ -34,7 +34,10 @@ Spark offers an abstraction called <a hr
<ul>
<li>
- <a
href="http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-214.pdf";>Shark:
SQL and Rich Analytics at Scale</a>. Reynold Xin, Joshua Rosen, Matei Zaharia,
Michael J. Franklin, Scott Shenker, Ion Stoica. <em>Technical Report
UCB/EECS-2012-214</em>. November 2012.
+ <a
href="http://www.cs.berkeley.edu/~matei/papers/2013/sosp_spark_streaming.pdf";>Discretized
Streams: Fault-Tolerant Streaming Computation at Scale</a>. Matei Zaharia,
Tathagata Das, Haoyuan Li, Timothy Hunter, Scott Shenker, Ion Stoica. <em>SOSP
2013</em>. November 2013.
+ </li>
+ <li>
+ <a
href="http://www.cs.berkeley.edu/~matei/papers/2013/sigmod_shark.pdf";>Shark:
SQL and Rich Analytics at Scale</a>. Reynold Xin, Joshua Rosen, Matei Zaharia,
Michael J. Franklin, Scott Shenker, Ion Stoica. <em>SIGMOD 2013</em>. June 2013.
</li>
<li>
<a
href="http://www.cs.berkeley.edu/~matei/papers/2012/hotcloud_spark_streaming.pdf";>Discretized
Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large
Clusters</a>. Matei Zaharia, Tathagata Das, Haoyuan Li, Scott Shenker, Ion
Stoica. <em>HotCloud 2012</em>. June 2012.
@@ -46,8 +49,6 @@ Spark offers an abstraction called <a hr
<a
href="http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf";>Resilient
Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster
Computing</a>. Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave,
Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica.
<em>NSDI 2012</em>. April 2012. <b>Best Paper Award</b> and <b>Honorable
Mention for Community Award</b>.
</li>
<li>
- <a
href="http://www.cs.berkeley.edu/~matei/papers/2011/tr_spark.pdf";>Resilient
Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster
Computing</a>. Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave,
Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica.
<em>Technical Report UCB/EECS-2011-82</em>. July 2011.</li>
- <li>
<a
href="http://www.cs.berkeley.edu/~matei/papers/2010/hotcloud_spark.pdf";>Spark:
Cluster Computing with Working Sets</a>. Matei Zaharia, Mosharaf Chowdhury,
Michael J. Franklin, Scott Shenker, Ion Stoica. <em>HotCloud 2010</em>. June
2010.
</li>
</ul>
Modified: incubator/spark/site/research.html
URL:
http://svn.apache.org/viewvc/incubator/spark/site/research.html?rev=1530857&r1=1530856&r2=1530857&view=diff
==============================================================================
--- incubator/spark/site/research.html (original)
+++ incubator/spark/site/research.html Thu Oct 10 04:50:39 2013
@@ -122,7 +122,7 @@
<h2>Spark Research</h2>
<p>
-Spark started as a research project at UC Berkeley in the <a
href="https://amplab.cs.berkeley.edu";>AMPLab</a>, which focuses on big data
analytics.
+Apache Spark started as a research project at UC Berkeley in the <a
href="https://amplab.cs.berkeley.edu";>AMPLab</a>, which focuses on big data
analytics.
</p>
<p class="noskip">
@@ -132,7 +132,7 @@ Our goal was to design a programming mod
<ul>
<li><em>Iterative algorithms</em>, including many machine learning
algorithms and graph algorithms like PageRank.</li>
<li><em>Interactive data mining</em>, where a user would like to load data
into RAM across a cluster and query it repeatedly.</li>
- <li><em>OLAP reports</em> that run multiple aggregation queries on the same
data.</li>
+ <li><em>Streaming applications</em> that maintain aggregate state over
time.</li>
</ul>
<p>
@@ -147,7 +147,10 @@ Spark offers an abstraction called <a hr
<ul>
<li>
- <a
href="http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-214.pdf";>Shark:
SQL and Rich Analytics at Scale</a>. Reynold Xin, Joshua Rosen, Matei Zaharia,
Michael J. Franklin, Scott Shenker, Ion Stoica. <em>Technical Report
UCB/EECS-2012-214</em>. November 2012.
+ <a
href="http://www.cs.berkeley.edu/~matei/papers/2013/sosp_spark_streaming.pdf";>Discretized
Streams: Fault-Tolerant Streaming Computation at Scale</a>. Matei Zaharia,
Tathagata Das, Haoyuan Li, Timothy Hunter, Scott Shenker, Ion Stoica. <em>SOSP
2013</em>. November 2013.
+ </li>
+ <li>
+ <a
href="http://www.cs.berkeley.edu/~matei/papers/2013/sigmod_shark.pdf";>Shark:
SQL and Rich Analytics at Scale</a>. Reynold Xin, Joshua Rosen, Matei Zaharia,
Michael J. Franklin, Scott Shenker, Ion Stoica. <em>SIGMOD 2013</em>. June 2013.
</li>
<li>
<a
href="http://www.cs.berkeley.edu/~matei/papers/2012/hotcloud_spark_streaming.pdf";>Discretized
Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large
Clusters</a>. Matei Zaharia, Tathagata Das, Haoyuan Li, Scott Shenker, Ion
Stoica. <em>HotCloud 2012</em>. June 2012.
@@ -159,8 +162,6 @@ Spark offers an abstraction called <a hr
<a
href="http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf";>Resilient
Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster
Computing</a>. Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave,
Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica.
<em>NSDI 2012</em>. April 2012. <b>Best Paper Award</b> and <b>Honorable
Mention for Community Award</b>.
</li>
<li>
- <a
href="http://www.cs.berkeley.edu/~matei/papers/2011/tr_spark.pdf";>Resilient
Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster
Computing</a>. Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave,
Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica.
<em>Technical Report UCB/EECS-2011-82</em>. July 2011.</li>
- <li>
<a
href="http://www.cs.berkeley.edu/~matei/papers/2010/hotcloud_spark.pdf";>Spark:
Cluster Computing with Working Sets</a>. Matei Zaharia, Mosharaf Chowdhury,
Michael J. Franklin, Scott Shenker, Ion Stoica. <em>HotCloud 2010</em>. June
2010.
</li>
</ul>
