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NoSQL Data Models

You're reading from   NoSQL Data Models Addresses severe issues related to NoSQL data models

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Product type Paperback
Published in Aug 2018
Publisher Wiley
ISBN-13 9781786303646
Length 278 pages
Edition 1st Edition
Languages
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Author (1):
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Olivier Pivert Olivier Pivert
Author Profile Icon Olivier Pivert
Olivier Pivert
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Toc

Table of Contents (11) Chapters Close

Preface
1 NoSQL Languages and Systems 2 Distributed SPARQL Query Processing: a Case Study with Apache Spark FREE CHAPTER 3 Doing Web Data: from Dataset Recommendation to Data Linking 4 Big Data Integration in Cloud Environments: Requirements, Solutions and Challenges 5 Querying RDF Data: a Multigraph-based Approach 6 Fuzzy Preference Queries to NoSQL Graph Databases 7 Relevant Filtering in a Distributed Content-based Publish/Subscribe System List of Authors
Index
End User License Agreement

6.4. Implementation challenges

Concerning the implementation issues, the following three main problems arise: (1) the implementation of the fuzzy data model if fuzzy data are considered; (2) the evaluation of queries extended by fuzzy preferences; and (3) the scalability of the query evaluation, which are discussed below.

6.4.1. Modeling fuzzy databases

Existing graph database management systems make it possible to only model crisp property graph databases, so the problem of modeling fuzzy databases in such systems arises. In the case of the property graph model like that considered in Neo4j, a set of properties (key–value pairs) can be bound to a node or an edge. Properties usually denote embedded data and meta-data associated with nodes or edges. A simple mechanism may then be used to simulate fuzzy graph databases in this crisp property graph model: we only have to attach to each edge of the property graph a supplementary arbitrary property called fdegree carrying the degree...

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