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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.
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Über die Autorin bzw. den Autor
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.
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Reusing calculated match results for MapReduce
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 52 pp. Englisch. Bestandsnummer des Verkäufers 9786209895449
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9786209895449
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Paperback. Zustand: new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786209895449
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Reusing calculated match results for MapReduce
Verlag:
Our Knowledge Publishing Mär 2026, 2026
ISBN 10: 6209895441
ISBN 13: 9786209895449
Neu
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Bestandsnummer des Verkäufers 9786209895449
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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. Bestandsnummer des Verkäufers 134877539
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