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author | Matei Alexandru Zaharia <matei@apache.org> | 2013-10-10 04:50:39 +0000 |
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committer | Matei Alexandru Zaharia <matei@apache.org> | 2013-10-10 04:50:39 +0000 |
commit | cc4b04b216320786bdcb949e5dfdaad5e4b73f5a (patch) | |
tree | cbdea329b913be04502ec8d7acb5f9226b7168e0 /site | |
parent | 35c233b9e64a2cf2f35a9c98706f89e0d64870d9 (diff) | |
download | spark-website-cc4b04b216320786bdcb949e5dfdaad5e4b73f5a.tar.gz spark-website-cc4b04b216320786bdcb949e5dfdaad5e4b73f5a.tar.bz2 spark-website-cc4b04b216320786bdcb949e5dfdaad5e4b73f5a.zip |
Update research paper links
Diffstat (limited to 'site')
-rw-r--r-- | site/research.html | 11 |
1 files changed, 6 insertions, 5 deletions
diff --git a/site/research.html b/site/research.html index f55827a64..5a6a7271d 100644 --- a/site/research.html +++ b/site/research.html @@ -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 model that supports a much wider class of a <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 href="http://www.cs.berkeley.edu/~matei/pa <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 href="http://www.cs.berkeley.edu/~matei/pa <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> |