Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Holger Pirk"'
Publikováno v:
Proceedings of the VLDB Endowment. 15:361-374
Single-node multi-core stream processing engines (SPEs) can process hundreds of millions of tuples per second. Yet making them fault-tolerant with exactly-once semantics while retaining this performance is an open challenge: due to the limited I/O ba
Autor:
Holger Pirk
Publikováno v:
ACM SIGMOD Record. 51:54-55
Motivation: Data science is increasingly collaborative. On the one hand, results need to be distributed, e.g., as interactive visualizations. On the other, collaboration in the data development process improves quality and timeliness. This can take m
Publikováno v:
SIGMOD Conference
Window aggregation queries are a core part of streaming applications. To support window aggregation efficiently, stream processing engines face a trade-off between exploiting parallelism (at the instruction/multi-core levels) and incremental computat
Publikováno v:
FPL
The International Conference on Field-Programmable Logic and Applications (FPL) 2019
The International Conference on Field-Programmable Logic and Applications (FPL) 2019
We present an efficient, high-throughput and scalable hardware design for accelerating the merge phase of the sort-merge join operation. Sort-merge join is one of the fundamental join algorithms and among the most frequently executed operations in re
Autor:
Holger Pirk
Publikováno v:
Proceedings of the 2019 International Conference on Management of Data.
Publikováno v:
Proceedings of the VLDB Endowment. 9:1707-1718
In-memory databases require careful tuning and many engineering tricks to achieve good performance. Such database performance engineering is hard: a plethora of data and hardware-dependent optimization techniques form a design space that is difficult
Autor:
Holger Pirk
Publikováno v:
Proceedings of the 2018 International Conference on Management of Data.
Autor:
Samuel Madden, Rahul Palamuttam, James J. Thomas, Deepak Narayanan, Matei Zaharia, Anil Shanbhag, Malte Schwarzkopf, Parimajan Negi, Shoumik Palkar, Pratiksha Thaker, Holger Pirk, Saman Amarasinghe
Modern analytics applications use a diverse mix of libraries and functions. Unfortunately, there is no optimization across these libraries, resulting in performance penalties as high as an order of magnitude in many applications. To address this prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63ee6ffc3017fb75554bb2e3cb2d7851
http://hdl.handle.net/10044/1/71236
http://hdl.handle.net/10044/1/71236
Autor:
Holger Pirk
Publikováno v:
ACM SIGMOD Record. 44:53-58
Computer system architecture has changed: an assembly of autonomous components has replaced the omnipotent CPU and its legion of dumb devices. Database Management System (DBMS) architecture, however, does not yet reflect this change: it is still domi
Publikováno v:
SIGMOD 2018
SIGMOD Conference
SIGMOD Conference
A common operation in many data analytics workloads is to find the top-k items, i.e., the largest or smallest operations according to some sort order (implemented via LIMIT or ORDER BY expressions in SQL). A naive implementation of top-k is to sort a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0c47cfdd860299dcf8fe3da72e8a912
http://hdl.handle.net/10044/1/58369
http://hdl.handle.net/10044/1/58369