Presented By O'Reilly and Cloudera
Make Data Work
March 28–29, 2016: Training
March 29–31, 2016: Conference
San Jose, CA
Todd Lipcon

Todd Lipcon
Engineer, Cloudera

Website | @tlipcon

Todd Lipcon is an engineer at Cloudera, where he primarily contributes to open source distributed systems in the Apache Hadoop ecosystem. Previously, he focused on Apache HBase, HDFS, and MapReduce, where he designed and implemented redundant metadata storage for the NameNode (QuorumJournalManager), ZooKeeper-based automatic failover, and numerous performance, durability, and stability improvements. In 2012, Todd founded the Apache Kudu project and has spent the last three years leading this team. Todd is a committer and PMC member on Apache HBase, Hadoop, Thrift, and Kudu, as well as a member of the Apache Software Foundation. Prior to Cloudera, Todd worked on web infrastructure at several startups and researched novel machine learning methods for collaborative filtering. Todd holds a bachelor’s degree with honors from Brown University.

Sessions

1:50pm–2:30pm Wednesday, 03/30/2016
Tags: real-time
Todd Lipcon (Cloudera)
Average rating: ****.
(4.68, 19 ratings)
Todd Lipcon explores the tradeoffs between real-time transactional access and fast analytic performance from the perspective of storage-engine internals. Todd also outlines Kudu, the new addition to the open source Hadoop ecosystem that complements HDFS and HBase to provide a new option for achieving fast scans and fast random access from a single API. Read more.
4:20pm–5:00pm Wednesday, 03/30/2016
Data Innovations

Location: 210 D/H
Moderated by:
Derrick Harris (Mesosphere)
Panelists:
Rob Peglar (Micron Technology, Inc), Milind Bhandarkar (Ampool, Inc.), Richard Probst (SAP), Todd Lipcon (Cloudera)
Average rating: ****.
(4.00, 5 ratings)
Years of research in nonvolatile memory systems is being productized and has started coming to market. These exciting new technologies promise lower power consumption and higher density for persistent storage. Will these hardware advances revolutionize the data ecosystem as we know it? This compelling panel of data-infrastructure thought leaders discusses the possibilities. Read more.