Zobrazeno 1 - 10
of 235
pro vyhledávání: '"Boncz, Peter"'
We provide an evaluation of an analytical workload in a confidential computing environment, combining DuckDB with two technologies: modular columnar encryption in Parquet files (data at rest) and the newest version of the Intel SGX Trusted Execution
Externí odkaz:
http://arxiv.org/abs/2405.11988
This demonstration presents a new Open Source SQL-to-SQL compiler for Incremental View Maintenance (IVM). While previous systems, such as DBToaster, implemented computational functionality for IVM in a separate system, the core principle of OpenIVM i
Externí odkaz:
http://arxiv.org/abs/2404.16486
Autor:
Battiston, Ilaria, Boncz, Peter
Publikováno v:
CEUR Workshop Proceedings 2023
In this research project, we investigate an alternative to the standard cloud-centralized data architecture. Specifically, we aim to leave part of the application data under the control of the individual data owners in decentralized personal data sto
Externí odkaz:
http://arxiv.org/abs/2312.12923
Autor:
Szárnyas, Gábor, Bebee, Brad, Birler, Altan, Deutsch, Alin, Fletcher, George, Gabb, Henry A., Gosnell, Denise, Green, Alastair, Guo, Zhihui, Hare, Keith W., Hidders, Jan, Iosup, Alexandru, Kiryakov, Atanas, Kovatchev, Tomas, Li, Xinsheng, Libkin, Leonid, Lin, Heng, Luo, Xiaojian, Prat-Pérez, Arnau, Püroja, David, Qi, Shipeng, van Rest, Oskar, Steer, Benjamin A., Szakállas, Dávid, Tong, Bing, Waudby, Jack, Wu, Mingxi, Yang, Bin, Yu, Wenyuan, Zhang, Chen, Zhang, Jason, Zhou, Yan, Boncz, Peter
Graph data management is instrumental for several use cases such as recommendation, root cause analysis, financial fraud detection, and enterprise knowledge representation. Efficiently supporting these use cases yields a number of unique requirements
Externí odkaz:
http://arxiv.org/abs/2307.04350
The LDBC Social Network Benchmark's Interactive workload captures an OLTP scenario operating on a correlated social network graph. It consists of complex graph queries executed concurrently with a stream of updates operation. Since its initial releas
Externí odkaz:
http://arxiv.org/abs/2307.04820
While database systems have long enjoyed a “free ride” with ever-increasing clock cycles of the CPU, in the last decade this increase stalled. On the computational side, we have seen an ever-increasing number of cores as well as the advent of spe
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A83921
https://tud.qucosa.de/api/qucosa%3A83921/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A83921/attachment/ATT-0/
Powerful abstractions such as dataframes are only as efficient as their underlying runtime system. The de-facto distributed data processing framework, Apache Spark, is poorly suited for the modern cloud-based data-science workloads due to its outdate
Externí odkaz:
http://arxiv.org/abs/2112.06280
Autor:
Boncz, Peter Alexander.
Proefschrift Universiteit van Amsterdam.
Met lit. opg.-Met samenvatting in het Nederlands.
Met lit. opg.-Met samenvatting in het Nederlands.
Externí odkaz:
http://dare.uva.nl/document/64315
Autor:
Boncz, Peter
We present an epidemiological model for the effectiveness of CoronaMelder, the Dutch digital contact tracing app developed on top of the Google/Apple Exposure Notification framework. We compare the effectiveness of CoronaMelder with manual contract t
Externí odkaz:
http://arxiv.org/abs/2105.15111
Autor:
Sakr, Sherif, Bonifati, Angela, Voigt, Hannes, Iosup, Alexandru, Ammar, Khaled, Angles, Renzo, Aref, Walid, Arenas, Marcelo, Besta, Maciej, Boncz, Peter A., Daudjee, Khuzaima, Della Valle, Emanuele, Dumbrava, Stefania, Hartig, Olaf, Haslhofer, Bernhard, Hegeman, Tim, Hidders, Jan, Hose, Katja, Iamnitchi, Adriana, Kalavri, Vasiliki, Kapp, Hugo, Martens, Wim, Özsu, M. Tamer, Peukert, Eric, Plantikow, Stefan, Ragab, Mohamed, Ripeanu, Matei R., Salihoglu, Semih, Schulz, Christian, Selmer, Petra, Sequeda, Juan F., Shinavier, Joshua, Szárnyas, Gábor, Tommasini, Riccardo, Tumeo, Antonino, Uta, Alexandru, Varbanescu, Ana Lucia, Wu, Hsiang-Yun, Yakovets, Nikolay, Yan, Da, Yoneki, Eiko
Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these a
Externí odkaz:
http://arxiv.org/abs/2012.06171