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  <div class="vevent h-event"> <h1 class="summary p-name">SnappyData - Real Time Operational Analytics with Apache Spark!</h1> <div class='date'><time class="dtstart dt-start" title="2015-12-01T18:00:00" datetime="2015-12-01T18:00:00">Tuesday, December 1, 2015 at 6pm</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202394893'><span class='fn org p-name'>Centrl Office</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">1355 NW Everett Street</div> <span class="locality p-locality">Portland</span> , <span class="region p-region">OR</span> <span class="postal-code p-postal-code">97209</span> <div class="country-name p-country-name">us</div> (<a href='https://maps.google.com/maps?q=1355%20NW%20Everett%20Street,%20Portland%20OR%2097209%20us'>map</a>) </div> </div> <div class="description p-description"> <p><img src="http://photos2.meetupstatic.com/photos/event/e/8/e/6/600_443519622.jpeg"></p> <p> </p><p></p> <p><b>Description </b></p> <p>Apache Spark has come a long ways since it began as a faster batch oriented map-reduce solution for Hadoop.  With support for streaming, machine learning and most recently SQL, Spark aspires to become a player in the realm of real time analytics at scale. </p> <p>However, much of its underpinnings remain batch oriented and unsuited for highly concurrent OLAP workloads. </p> <p>In this talk, we will describe how we are innovating and renovating Spark's core underpinnings to make it suitable for real time operational analytics, helping create a unified platform that supports row and column data, high concurrency and approximate query processing at scale.</p> <p></p> <p><b>Agenda</b></p> <p>6:00 – 6:15 Welcome and Networking</p> <p>6:15 – 7:15 Presentation by Jags Ramnarayan</p> <p>7:15 – 8:00 Food, Drinks & Discussion</p> <p><b>Presenter</b></p> <p><img src="http://photos3.meetupstatic.com/photos/event/e/8/f/9/600_443519641.jpeg"></p> <p><a href="https://www.linkedin.com/profile/view?id=6206657&authType=name&authToken=8Y25&trk=miniprofile-name-link"></a></p> <p><a href="https://www.linkedin.com/in/jhlch"></a><a href="https://www.linkedin.com/in/jagsr">Jags Ramnarayan</a> is the chief product visionary for SnappyData. </p> <p>Jags is the Chief Architect for “fast data” products(GemFire) at Pivotal and has served in the extended leadership team of the company. At Pivotal and previously at VMWare he led the technology direction for its high performance distributed data Grid and in-memory DB products. </p> <p>He has spent more than two decades in this industry and has a bachelors degree in computer science and a masters degree in management of science and technology.</p> <p><br><b>Sponsors</b></p> <p></p> <p><a href="http://www.snappydata.io/">Snappy Data</a> is the presenter of the event and sponsor for food and drinks.</p> <p><img src="http://www.emcworld.com/images/sponsor_logos/logo_sponsor_pivotal.png"></p> <p><a href="http://pivotal.io/">Pivotal</a> is the sponsor for the hosting fees.</p> <p></p> <p><a href="http://centrloffice.com/">CentrlOffice</a> is the host for this event.</p> </div> <h3>Links</h3> <ul> <li><a class="url u-url" href="http://www.meetup.com/Hadoop-Portland/events/226330909/">Website</a></li> </ul> </div>