Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
|
EL
| URI | http://purl.tuc.gr/dl/dias/C645792E-66E5-4E59-BB7F-4457C13496AB | - |
| Αναγνωριστικό | https://doi.org/10.1145/3465480.3467842 | - |
| Αναγνωριστικό | https://dl.acm.org/doi/10.1145/3465480.3467842 | - |
| Γλώσσα | en | - |
| Μέγεθος | 2 pages | en |
| Τίτλος | Real-time processing of geo-distributed financial data | en |
| Δημιουργός | Kontaxakis Antonios | en |
| Δημιουργός | Κονταξακης Αντωνιος | el |
| Δημιουργός | Deligiannakis Antonios | en |
| Δημιουργός | Δεληγιαννακης Αντωνιος | el |
| Δημιουργός | Arndt Holger | en |
| Δημιουργός | Burkard Stefan | en |
| Δημιουργός | Kettner Claus-Peter | en |
| Δημιουργός | Pelikan Elke | en |
| Δημιουργός | Noack Kathleen | en |
| Εκδότης | Association for Computing Machinery (ACM) | en |
| Περίληψη | Enabling real-time processing of financial data streams is extremely challenging, especially considering that typical operations that interest investors often require combining data across (a potentially quadratic number of) different pairs of stocks. In this paper we present the architecture and the components of our system for the real-time processing of geo-distributed financial data at scale. Our system can scale to larger resources and utilizes a Synopses Data Engine in order to efficiently handle complex cross-stock queries, such as the ones required to detect systemic risk or to help forecast the value of some stock. The rich set of supported operations is depicted at the Visual Analytics component of our system. | en |
| Τύπος | Αφίσα σε Συνέδριο | el |
| Τύπος | Conference Poster | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2023-06-23 | - |
| Ημερομηνία Δημοσίευσης | 2021 | - |
| Θεματική Κατηγορία | Real-time processing | en |
| Θεματική Κατηγορία | Financial data | en |
| Θεματική Κατηγορία | Flink | en |
| Βιβλιογραφική Αναφορά | A. Kontaxakis, A. Deligiannakis, H. Arndt, S. Burkard, C.-P. Kettner, E. Pelikan, and K. Noack, “Real-time processing of geo-distributed financial data,” in Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems (DEBS 2021), virtual event, 2021, pp. 190–191, doi: 10.1145/3465480.3467842. | en |
Copyright © DIAS 2013
