2017 Program Schedule

The fourth annual Accumulo Summit was held on October 16th, 2017 in Columbia, Maryland.

8:00–9:00 — Terrace Ballroom Lobby
Registration
9:00–10:00 — Terrace Ballroom Lobby
  • Opening Remarks
    Dan Hood, ClearEdge IT Solutions
  • State of Accumulo 2017
    Aaron Cordova, Koverse
    Adam Fuchs, Sqrrl
    Keynote
10:00–10:15 — Terrace Ballroom Lobby
Break & Morning Snack
10:15–10:50 — Terrace Ballroom A/B
Practical Kerberos
Josh Elser, Hortonworks
Security
10:15–10:50 — Terrace Ballroom C/D
Choosing a Strategy for Accumulo Table Designs
Aaron Cordova, Koverse
Design Performance
11:00–10:35 — Terrace Ballroom A/B
Accumulo and Ranger Integration
John Highcock, Hortonworks
Marcus Waineo, Hortonworks
Security
11:00–10:35 — Terrace Ballroom C/D
Timely Year Two: Lessons Learned Building a Scalable Metrics Analytic System
Drew Farris, Booz Allen Hamilton
Bill Oley, Booz Allen Hamilton
APIs / Frameworks
11:45–12:20 — Terrace Ballroom A/B
Data-Defined Typed Schema Generation in Accumulo
Chad Hardin, Koverse
Design
11:45–12:20 — Terrace Ballroom C/D
MiNiFi and Accumulo Sitting in a Tree
Marc Parisi
APIs / Frameworks
12:30–1:30 — Terrace Ballroom Lobby
Terrace Ballroom A/B, C/D, and Restaurant
1:30–2:05 — Terrace Ballroom A/B
Choosing a Strategy for Accumulo Table Designs
Aaron Cordova, Koverse
Design Performance
1:30–2:05 — Terrace Ballroom C/D
Presto/Accumulo: Lessons Learned
Adam Shook, Datacatessen
APIs / Frameworks
2:15–2:50 — Terrace Ballroom A/B
Performance Modeling and Simulation for Accumulo Applications
Adam Fuchs, Sqrrl
Performance
2:15–2:50 — Terrace Ballroom C/D
Accumulo and the Convergence of Machine Learning, Big Data, and Supercomputing
Jeremy Kepner, MIT
Use Case
2:50–3:30 — Terrace Ballroom Lobby
Break & Afternoon Snack
3:30–4:05 — Terrace Ballroom A/B
Lessons Learned: Optimizing Accumulo as a Backend for User Applications
Zach Radtka, Miner & Kasch
Performance Use Case
3:30–4:05 — Terrace Ballroom C/D
Comparing Accumulo, Cassandra, and HBase
Aaron Cordova, Koverse
APIs / Frameworks Use Case
4:15–4:50 — Terrace Ballroom A/B
Turning Your Iterators Up to 11: New Features for Complex Iterator Implementations
Ivan Bella, ASRC
Performance
4:15–4:50 — Terrace Ballroom C/D
Case Study: Building a Production Recommendation Engine on Accumulo
Gadalia O'Bryan, Koverse
Use Case
5:00–7:00 — Terrace Ballroom Lobby
Cocktail Hour & Networking