The talk will be a description of how MapR’s architectural advances allow significant improvements in speed, reliability and scalability over stock Hadoop. This will include a dive into the MapR file system and a discussion of how the map-reduce layer has been changed and the impact on other Hadoop eco-system components. This will include actual test results.
In the second section of my talk, I will describe how this new architecture has surprising consequences. In particular, I will show how tasks like machine learning, data visualization and search indexing can all work better on the MapR platform.
Ted has held Chief Scientist positions at Veoh Networks, ID Analytics and at MusicMatch, (now Yahoo Music). Ted is responsible for building the most advanced identity theft detection system on the planet, as well as one of the largest peer-assisted video distribution systems and ground-breaking music and video recommendations systems. Ted has 15 issued and 15 pending patents and contributes to several Apache open source projects including Hadoop, Zookeeper and Hbase. He is also a committer for Apache Mahout. Ted earned a BS degree in electrical engineering from the University of Colorado; a MS degree in computer science from New Mexico State University; and a Ph.D. in computing science from Sheffield University in the United Kingdom. Ted also bought the drinks at one of the very first Hadoop User Group meetings.