Anzeige
Erschienen in:
2013 | OriginalPaper | Buchkapitel
An Algorithm for Querying Linked Data Using Map-Reduce
verfasst von : Manolis Gergatsoulis, Christos Nomikos, Eleftherios Kalogeros, Matthew Damigos
Erschienen in: Data Management in Cloud, Grid and P2P Systems
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, we exploit the widely used Map-Reduce framework and propose a generic two-phase, Map-Reduce algorithm for querying large amount of linked data. The algorithm is based on the idea that the data graph can be arbitrarily partitioned into
graph segments
which can be stored in different nodes of a cluster of commodity computers. To answer a user query
Q
,
Q
is also decomposed into a set of subqueries. In the first phase, the subqueries are applied to each graph segment, in isolation, and intermediate results are computed. The intermediate results are combined in the second phase to obtain the answers of the query
Q
. The proposed algorithm computes the answers to a given query correctly, independently of a) the data graph partitioning, b) how graph segments are stored, c) the query decomposition, and d) the algorithm used for calculating (partial) results.