Anoop Dawar is responsible for worldwide product, solutions and services marketing at MapR. As a cross-functional technology leader, Anoop has deep experience in product development, product management and marketing. Prior to this role, Anoop was VP of Product Management at MapR leading core data platform as well as the Hadoop/Spark stack. Anoop comes to MapR with over a decade of experience leading engineering and product management teams at Aerohive (HIVE) and Cisco (CSCO). Anoop's engineering approach to marketing problems stems from his deep background in both technology and business as a practitioner and a student. Anoop received a Masters in Computer Science from University of Texas at Austin and a Masters in Business Administration from The Wharton School of the University of Pennsylvania.
In 2015, MapR shipped three significant core releases : 4.0.2 in January, 4.1 in April, 5.0 and the GA version of Apache Drill in July. While all this was happening, many of my colleagues in engineering (who’ve demonstrated a whole new level of ingenuity and multitasking) were also working on one of the biggest releases in the history of MapR—the converged data platform release (AKA, MapR 5.1).
In this week's Whiteboard Walkthrough, Anoop Dawar, Senior Product Director at MapR, shows you the basics of Apache Spark and how it is different from MapReduce.
As part of working at MapR, we live and breathe Apache Hadoop. And we use Hadoop to help customers solve difficult business problems that would be intractable otherwise. Last year, about six months after shipping our first version of Hadoop 2.x with YARN, multiple customers asked us to consider working with Apache Mesos. Our early response was that of curiosity. Why are multiple customers asking us to work with Mesos when we just released YARN?
In this blog series, we’re showcasing the top 10 reasons customers are turning to MapR in order to create new insights and optimize their data-driven strategies. Here’s reason #4: MapR provides true multi-tenancy with job isolation, volumes, quotas, data and job placement control, including for YARN.
To get real with Hadoop, you need a real enterprise-ready platform. Join us as we begin the countdown of the 10 top reasons our customers choose MapR. Reason #10....Enterprise-grade security. Security has always been important with enterprise customers, but today it’s non-negotiable.
On the heels of the recent Spark stack inclusion announcement, here is some more fresh powder (For non-skiers, that’s fresh snow on a mountain).
MapR Distribution of Apache Hadoop: 4.0.0 Beta
As many of you may recall, YARN was first released in October 2013 and gathered a lot of buzz in the later part of the year. On February 20th, the community voted to release the next version of YARN with Hadoop 2.3.0. We are delighted at the progress that has been made with YARN in particular. Here are the Hadoop 2.3.0 release notes from the Apache Hadoop website.
It gives me immense pleasure to write this blog on behalf of all of us here at MapR to announce the release of Hadoop 2.x, including YARN, on MapR. Much has been written about Hadoop 2.x and YARN and how it promises to expand Hadoop beyond MapReduce. I will give a quick summary before highlighting some of the unique benefits of Hadoop 2.x and YARN in the MapR Distribution for Hadoop.
MapR has always been in the business of making Hadoop easier, and we believe we've made another big step forward with the MapR Sandbox for Hadoop. The MapR Sandbox gives developers and administrators the fastest and easiest way to get up to speed on Hadoop.
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