Apache Hadoop has been synonymous with open source big data analytics for over a decade. With the 3.0 major release, Apache Hadoop continues to evolve with the addition of significant new features like HDFS erasure coding, YARN Timeline Service v2, and MapReduce task-level optimization. Together, these new features improve the performance, scalability, and multitenancy capabilities of Hadoop.
Andrew Wang and Daniel Templeton offer an overview of new features and discuss current release management status and community testing efforts dedicated to making Hadoop 3.0 the best Hadoop major release yet.
Daniel Templeton has a long history in high-performance computing, open source communities, and technology evangelism. Today Daniel works on the YARN development team at Cloudera, focused on the resource manager, fair scheduler, and Docker support.
Andrew Wang is a software engineer on the HDFS team at Cloudera. Previously, he was a graduate student in the AMPLab at the University of California, Berkeley, advised by Ion Stoica, where he worked on research related to in-memory caching and quality of service. In his spare time, he enjoys going on bike rides, cooking, and playing guitar.
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