The aim of this project is to extend an existing project, called Dedoop, with additional features. Dedoop enables similarities to be identified between pairs of entities within large datasets. The data is processed using MapReduce-based methods. Identifying similarities is a computation that requires a great deal of processing time. If a change has been made to one or more entities in the original set, the calculation must be restarted. The aim of this thesis is to avoid having to repeat the comparisons in full and to find a way, using previously calculated match results, to limit the process to only those specific subsets that require recalculation.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Sergej Sintschilin. I was born on 8 December 1987 in Tomsk. I moved to Germany in 2001. I am interested in computer science and data management in general. In 2016, I completed my Master of Science degree at the University of Leipzig. I currently work at sofistiq.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: California Books, Miami, FL, USA
Zustand: New. Artikel-Nr. I-9786209895449
Anzahl: Mehr als 20 verfügbar
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Reusing calculated match results for MapReduce | Hadoop's MapReduce | Sergej Sintschilin | Taschenbuch | Englisch | 2026 | Our Knowledge Publishing | EAN 9786209895449 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Artikel-Nr. 134877539
Anzahl: 5 verfügbar