All Videos Tagged MapR (Data Science Central) - Data Science Central 2020-10-29T17:33:02Z https://www.datasciencecentral.com/video/video/listTagged?tag=MapR&rss=yes&xn_auth=no DSC Webinar Series: When is the right time for real-time? Architectural best practices for Hadoop tag:www.datasciencecentral.com,2015-08-20:6448529:Video:312963 2015-08-20T21:13:28.929Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-when-is-the-right-time-for-real-time"><br /> <img alt="Thumbnail" height="180" src="https://storage.ning.com/topology/rest/1.0/file/get/2781532334?profile=original&amp;width=240&amp;height=180" width="240"></img><br /> </a> <br></br>Real-time processing is an important part of your Hadoop architecture, but is it always the best approach to analytics? Join us for our latest DSC Webinar with experts from MapR and Think Big, as we delve into the decision making process around Hadoop real-time and batch processes. You will learn the ins and outs of low-latency design for analytics, as… <a href="https://www.datasciencecentral.com/video/dsc-webinar-when-is-the-right-time-for-real-time"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781532334?profile=original&amp;width=240&amp;height=180" width="240" height="180" alt="Thumbnail" /><br /> </a><br />Real-time processing is an important part of your Hadoop architecture, but is it always the best approach to analytics? Join us for our latest DSC Webinar with experts from MapR and Think Big, as we delve into the decision making process around Hadoop real-time and batch processes. You will learn the ins and outs of low-latency design for analytics, as well as see how these designs get implemented in the real world.<br /> <br /> You will learn:<br /> <br /> Useful design patterns for building your Hadoop stack that best serves low-latency requirements<br /> Pitfalls to avoid when choosing your real-time processing option<br /> Real customer examples highlighting decision-making processes for both real-time and batch processing<br /> Panelist:<br /> Steve Wooledge, Vice President, Product Marketing -- MapR<br /> Bill Kornfeld Director, R&amp;D -- Think Big, a Teradata Company<br /> <br /> Hosted by: Bill Vorhies, Editorial Director -- Data Science Central Let Spark Fly: Advantages and Use Cases for Spark on Hadoop tag:www.datasciencecentral.com,2014-04-29:6448529:Video:165232 2014-04-29T21:41:20.603Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/let-spark-fly-advantages-and-use-cases-for-spark-on-hadoop"><br /> <img alt="Thumbnail" height="180" src="https://storage.ning.com/topology/rest/1.0/file/get/2781551520?profile=original&amp;width=240&amp;height=180" width="240"></img><br /> </a> <br></br>Apache Spark is currently one of the most active projects in the Hadoop ecosystem, and as such, there’s been plenty of hype about it in recent months, but how much of the discussion is marketing spin? And what are the facts? MapR and Databricks, the company that created and led the development of the Spark stack, will cut through the noise to… <a href="https://www.datasciencecentral.com/video/let-spark-fly-advantages-and-use-cases-for-spark-on-hadoop"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781551520?profile=original&amp;width=240&amp;height=180" width="240" height="180" alt="Thumbnail" /><br /> </a><br />Apache Spark is currently one of the most active projects in the Hadoop ecosystem, and as such, there’s been plenty of hype about it in recent months, but how much of the discussion is marketing spin? And what are the facts? MapR and Databricks, the company that created and led the development of the Spark stack, will cut through the noise to uncover practical advantages for having the full set of Spark technologies at your disposal and reveal the benefits for running Spark on Hadoop<br /> <br /> In today’s webinar, you will get a quick introduction to the Spark ecosystem and learn:<br /> • How you can leverage the enhanced functionality Spark provides to Hadoop to solve for your specific use cases<br /> • How easy it is to develop applications and models using Spark APIs<br /> • Why MapR is the only distribution that supports the complete Spark stack<br /> • What unique advantages you gain from having a complete Spark stack on Hadoop