Office Hour with the Berkeley Data Analytics Team

Expo Hall (Table C)
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We will answer questions related to the Berkeley Data Analytics Stack (BDAS), including:

- Spark, a high-speed cluster computing system compatible with Hadoop that can outperform it by up to 100x

- Shark, an Apache Hive compatible warehouse system that can be 100x faster than Hive without modification to the data and queries

- Streaming, a high-throughput, fault-tolerant streaming solution built on top of Spark.

Photo of Reynold Xin

Reynold Xin

Databricks

Reynold Xin is a PhD student in the AMP Lab at UC Berkeley. He leads the research and development of two open source systems: Shark, an analytical SQL engine that is up to 100X faster than Apache Hive; and SparkGraph, a distributed graph computation engine. He is a recipient of Best Demo Award from SIGMOD 2012 and Best Demo Award from VLDB 2011. Before graduate school, he worked on ads infrastructure at Google and distributed databases at IBM.

Photo of Matei Zaharia

Matei Zaharia

Databricks

Matei Zaharia started the Spark project at UC Berkeley and is currently CTO of Databricks. He serves as Spark’s vice president at Apache. In spring 2015, he is also beginning an assistant professor position at MIT.

Ion Stoica

UC Berkeley

Ion Stoica is a Professor of Computer Science at UC Berkeley, where he does research on cloud computing and networked computer systems. Past work includes the Dynamic Packet State (DPS), Chord DHT, Internet Indirection Infrastructure (i3), declarative networks, replay-debugging, and multi-layer tracing in distributed systems. His current research includes resource management and scheduling for data centers, cluster computing frameworks, and network architectures. He is the recipient of a SIGCOMM Test of Time Award, the CoNEXT Rising Star Award, the PECASE Award, and the ACM doctoral dissertation award. Ion also co-founded Conviva, a startup to commercialize technologies for large scale video distribution.

Photo of Andy Konwinski

Andy Konwinski

UC Berkeley

Andy Konwinski is a postdoc in the AMPLab at UC Berkeley focused on large scale distributed computing and cluster scheduling. He co-created and is a committer on the Apache Mesos project that has been adopted by Twitter as their private cloud platform. He also worked with systems engineers and researchers at Google on Omega, their next generation cluster scheduling system. More recently, he lead the AMP Camp Big Data Bootcamp and has been contributing to the Spark project.

Photo of Tathagata Das

Tathagata Das

Databricks

Tathagata Das is an Apache Spark committer and a member of the PMC. He is the lead developer behind Spark Streaming, which he started while a PhD student in the UC Berkeley AMPLab, and is currently employed at Databricks. Prior to Databricks, Tathagata worked at the AMPLab, conducting research about data-center frameworks and networks with Scott Shenker and Ion Stoica.

Photo of Patrick Wendell

Patrick Wendell

Databricks

Patrick Wendell is a cofounder of Databricks as well as a founding committer and PMC member of Apache Spark. Patrick has acted as release manager for several Spark releases in addition to maintaining several subsystems of Spark’s core engine. At Databricks, Patrick directs the company’s maintenance and development of Spark.

Patrick holds an MS in computer science from UC Berkeley, where his research focused on low-latency scheduling for large-scale analytics workloads, and a BSE in computer science from Princeton University.

Shivaram Venkataraman

UC Berkeley

Shivaram Venkataraman is a fifth year PhD student at the University of California, Berkeley and works with Mike Franklin and Ion Stoica at the AMP Lab. His research
interests are in design of storage systems and analytics platforms for big-data applications. Before coming to Berkeley, he completed his M.S at the University of Illinois, Urbana-Champaign.

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