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Andy Konwinski

Andy Konwinski
UC Berkeley

| Attendee Directory Profile

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.

Sessions

9:00am Tuesday, 02/26/2013
An Introduction to the Berkeley Data Analytics Stack (BDAS) Featuring Spark, Spark Streaming, and Shark - Part 1
Beyond Hadoop Ballroom G
Tutorial Please note: to attend, your registration must include Tutorials on Tuesday.
Ion Stoica (UC Berkeley), Matei Zaharia (UC Berkeley), Reynold Xin (UC Berkeley), Shivaram Venkataraman (UC Berkeley), Andy Konwinski (UC Berkeley), Tathagata Das (University of California Berkeley)
Average rating: *****
(5.00, 3 ratings)
An introduction Spark and Shark, two components of the open-source Berkeley Data Analytics Stack (BDAS) in development at UC Berkeley. Spark is a high-speed cluster computing system compatible with Hadoop that can outperform it by up to 100x. Shark is a port of Apache Hive onto Spark that is fully compatible with, and up to 100x faster than, Hive. Read more.
1:30pm Tuesday, 02/26/2013
Hands-on with BDAS - Learn Spark, Spark Streaming and Shark via Real Data Analysis - Part 2
Beyond Hadoop Room 204
Tutorial Please note: to attend, your registration must include Tutorials on Tuesday.
Matei Zaharia (UC Berkeley), Reynold Xin (UC Berkeley), Andy Konwinski (UC Berkeley), Tathagata Das (University of California Berkeley), Patrick Wendell (UC Berkeley)
Average rating: ****.
(4.00, 1 rating)
Building on our previous tutorial introducing BDAS, the open-source Berkeley Data Analytics Stack, in this tutorial we will provide each audience member with a Spark/Shark cluster on EC2 and walk through hands-on coding examples. Lessons will cover the Spark and Shark command line interfaces, writing a standalone program, and data clustering using a distributed machine learning algorithm on Spark. Read more.
10:10am Wednesday, 02/27/2013
Office Hour with the Berkeley Data Analytics Team
Expo Hall (Table C)
Reynold Xin (UC Berkeley), Matei Zaharia (UC Berkeley), Ion Stoica (UC Berkeley), Andy Konwinski (UC Berkeley), Tathagata Das (University of California Berkeley), Patrick Wendell (UC Berkeley), Shivaram Venkataraman (UC Berkeley)
Average rating: ***..
(3.00, 1 rating)
. Read more.

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