"Strata + Hadoop World San Jose 2015" entries

Three projects from UC Berkeley’s AMPLab have been keenly adopted by industry: Apache Mesos, Apache Spark, and Tachyon. As an early user, it’s been fun to watch Spark go from an academic lab to the most active open source project in big data. In my recent travels, I’ve met Spark users from companies of all sizes and and from many industries. I’ve also spoken with companies that came of age before Spark was available or mature enough, and many are replacing homegrown tools with Spark (Full disclosure: I’m an advisor to Databricks, a start-up commercializing Apache Spark..)

A few months ago, I spoke with UC Berkeley Professor and Databricks CEO Ion Stoica about the early days of Spark and the Berkeley Data Analytics Stack. Ion noted that by the time his students began work on Spark and Mesos, his experience at his other start-up Conviva had already informed some of the design choices:

“Actually, this story started back in 2009, and it started with a different project, Mesos. So, this was a class project in a class I taught in the spring of 2009. And that was to build a cluster management system, to be able to support multiple cluster computing frameworks like Hadoop, at that time, MPI and others. To share the same cluster as the data in the cluster. Pretty soon after that, we thought about what to build on top of Mesos, and that was Spark. Initially, we wanted to demonstrate that it was actually easier to build a new framework from scratch on top of Mesos, and of course we wanted it to be also special. So, we targeted workloads for which Hadoop at that time was not good enough. Hadoop was targeting batch computation. So, we targeted interactive queries and iterative computation, like machine learning. Read more…