direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Inhalt des Dokuments

TU Berlin and DFKI Data Management Systems Researchers Offer Presentations at the code.talks Developer Conference

Welcome Session of code.talks 2019
Lupe [1]

This year’s code.talks developer conference was held on the 24th and 25th of October in Hamburg, Germany. The sold-out conference with 1600 participants has grown to be one of Europe’s largest developer conferences. With over 600 talk submissions, conference organizers curated a program comprised of 120 talks and panels and over 130 speakers and panelists. Unlike research conferences, code.talks does not target researchers, but rather developers instead. Their main objective is to provide developers with inspiring experiences. Talks cover a wide range of topics, including user stories, use-cases, developer experiences, creative solutions, big data architectures, web technologies, programming tutorials, system presentations, and research, among others.

Participants discussing in front of the venue
Lupe [2]

Philipp Grulich and Jonas Traub researchers in the Database Systems and Information Management Group at TU Berlin (TUB) and the Intelligent Analytics for Massive Data Research Department at the German Research Center for Artificial Intelligence (DFKI) contributed to the Big Data track. In the panel discussion on GDPR – Who cares? Heike Wolters (Xing) discussed experiences, challenges, and opportunities related to the EU GDPR (General Data Protection Regulation) with Verena Grentzenberg (DLA PIPER), Wolfram Wingerath (Universität Hamburg), and Jonas Traub. Additionally, in their talk entitled Scotty: Efficient Window Aggregation for your Stream Processing System, Philipp and Jonas jointly from TUB und DFKI presented their work on the Scotty Window Processor, which enables high-throughput window aggregations in stream processing systems. The talks introduced the concept of stream slicing, in order to share partial aggregates among overlapping windows. Scotty works as a drop-in replacement for window operators in stream processing engines, like Apache Flink and Storm. With its Apache Beam connector, Scotty can also be integrated into Google Cloud Dataflow. Scotty is the result of a cooperative work, which originated at KTH Stockholm and RISE SICS, with the Cutty Project [1] and evolved to the generally applicable solution, which received the best paper award at EDBT 2019 [2,3].

More information about code.talks, including presentation slides and video recordings will soon be available on the official code.talks website: https://www.codetalks.de [3].



[1] “Cutty: Aggregate Sharing for User-Defined Windows,” Paris Carbone, Jonas Traub, Asterios Katsifodimos, Seif Haridi, and Volker Markl, Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (CIKM '16), October 24 - 28, 2016, Indianapolis, Indiana, USA.

[2] “Efficient Window Aggregation with General Stream Slicing,” Jonas Traub, Philipp Grulich, Alejandro Rodríguez Cuéllar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, and Volker Markl, The 22nd International Conference on Extending Database Technology (EDBT), March 2019.

[3] “Scotty: Efficient Window Aggregation for out-of-order Stream Processing,” Jonas Traub, Philipp M. Grulich, Alejandro Rodríguez Cuellar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, and Volker Markl, The 34th IEEE International Conference on Data Engineering (ICDE), April 2018.

------ Links: ------

Zusatzinformationen / Extras


Schnellnavigation zur Seite über Nummerneingabe

Copyright TU Berlin 2008