Hasso-Plattner-Institut
Prof. Dr. Tilmann Rabl
 

Thomas Bodner

Ph.D. Student
Email: thomas.bodner(at)hpi.de
Phone: +49-(0)331 5509 - 3934
Office: Campus II, F-1.06
Office Hours: Just stop by or mail/call ahead for an appointment
Profiles: DBLP, Google ScholarResearchGate, GitHubLinkedIn

I am a Computer Science Ph.D. student in the Data Engineering Systems Group at HPI, co-advised by Tilmann Rabl and Hasso Plattner. The goal of my research is to make data systems cheaper and faster through the unique capabilities of modern cloud environments. I am particularly interested in all aspects around query processing on serverless cloud infrastructure. Before joining HPI, I have built data systems at SAP, TU Berlin, UC Irvine, and IBM.

Research Interests

Elastic Query Processing on Serverless Infrastructure

Enterprises increasingly run the applications supporting their business processes in the cloud. Application data residing in the cloud expand the importance of cloud-based analytical workloads, which require provisioned infrastructure before any query processing can begin. Resource provisioning can be difficult for these workloads because they are often unpredictable and ad-hoc in nature. Overprovisioning and reduced cost-efficiency are the norm to avoid disruption of performance due to insufficient resources.

Recently, cloud providers have introduced means to allocate and bill fine-granular units of resources with function-as-a-service (FaaS) compute platforms and shared object storage systems. We evaluate this so-called serverless infrastructure regarding its performance elasticity and variability. Based on our findings, we build the Skyrise serverless query processor that interhits the elastic scalability of its underlying FaaS infrastructure while it deals with the limitations and inefficiencies. Skyrise enables cost-efficient, interactive analytics on infrequently accessed data, a workload for which conventionally provisioned database systems are idle most of the time and thus not viable.

Publications

  • Doppler: Understanding Serverless Query Execution @ SIGMOD BiDEDE 2022
    Thomas Bodner, Tobias Pietz, Lars Jonas Bollmeier, Daniel Ritter
  • Elastic Query Processing on Function as a Service Platforms @ VLDB PhD Workshop 2020
    Thomas Bodner
  • Towards Scalable Real-time Analytics: An Architecture for Scale-out of OLXP Workloads @ VLDB 2015
    Anil Goel, Jeffrey Pound, Nathan Auch, Peter Bumbulis, Scott MacLean, Franz Färber, Francis Gropengiesser, Christian Mathis, Thomas Bodner, Wolfgang Lehner
  • Myriad: Parallel Data Generation on Shared-nothing Architectures @ PACT ASBD 2011
    Alexander Alexandrov, Berni Schiefer, John Poelman, Stephan Ewen, Thomas Bodner, Volker Markl

Patents

  • Generation of Bots Based on Observed Behavior
    Gregor Berg, Andre Niklas Wenz, Bernhard Hoeppner, Thomas Bodner, Olga Cherepanova, Lasse Steffen, Jan Siebert, David Hennemann, Pascal Schulze, Konstantin Dobler, Kris-Fillip Kahl, Paul Udo Beneke, Philipp Bernhard Hoberg
    > US 2019
  • An Algorithm for Consistent Replication of Log-Structured Data
    Peter Bumbulis, Jeffrey Pound, Nathan Auch, Anil Goel, Matthias Ringwald, Thomas Bodner, Scott MacLean 
    > EU 2017 > US 2016

Students

Paper Supervision:

Master's Thesis Supervision:

  • Cost-aware Pruning with Filters in Serverless Data Management, Timon Millich, 2022
  • Serverless Maintenance of Database Statistics and Cached Query Results, Pascal Schulze, 2022
  • Cost-efficiency and Robustness in Serverless Join Processing, David Justen, 2021
  • Query Compilation for Distributed Execution with Cloud Functions, Julian Menzler, 2021
  • Straggler Mitigation in Distributed Query Execution on Cloud Functions, Fabian Engel, 2021
  • Elastic Query Execution via Short-lived and Stateless Cloud Functions, Jan Mensch, 2020
  • Network Request Handling in Database Systems, Toni Stachewicz, 2019
  • Data-dependent Implicit Authorizations for Fine-grained Database Access Control, Dennis Hempfing, 2018
  • Pushing Down User-defined Functionality in Distributed Log-centric Big Data Stacks, Josephine Rückert, 2017

Teaching

Lectures:

  • Big Data Systems (2023)
  • Trends and Concepts in the Software Industry I (2021202020192018)

Seminars:

  • Develop your own Database (2023, 20222019)
  • Joint Database Systems Seminar with TU Darmstadt (2022)
  • Research and Implementation of Database Concepts (202220212020)
  • Trends and Concepts in the Software Industry II (2020)

Master's Projects:

  • Building an Elastic Query Engine on Serverless Cloud Infrastructure (2021)
  • Performance Engineering for Cloud-based Database Systems (2020)

Bachelor's Projects: