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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15684

Title: Conjunctive Regular Path Queries in MapReduce
Authors: Ketsman, Bas
Advisors: NEVEN, Frank
Issue Date: 2013
Publisher: tUL
Abstract: In the current big data era, in which we are overloaded with huge amounts of data, there is a large demand for alternatives to traditional querying systems. In our context, big data refers to the petabyte scale data analysis to which industry and academia are ex- posed today; and, where hundreds or thousands of machines, running in parallel, are required to finish computations in a reasonable amount of time. However, the current data landscape also has a complex and non-traditional structure, which typically fits well into the graph model. In semi-structured data, the traditional relational query languages fall short. Hence, we consider the conjunctive regular path queries (CRPQs); a simple, but reasonably expressive language for querying graph data. This thesis is about the eval- uation of CRPQs in MapReduce, a framework that provides a programming abstraction that enables the design of algorithms that can be executed automatically on a cluster of machines in a fault-tolera
Notes: master in de informatica-databases
URI: http://hdl.handle.net/1942/15684
Category: T2
Type: Theses and Dissertations
Appears in Collections: Master theses

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