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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

6.2. Preliminary statements

We first introduce some background notions concerning graph databases in section 6.2.1 and then fuzzy set theory in section 6.2.2.

6.2.1. Graph databases

We present the graph data model in section 6.2.1.1 and explain how to query such a graph database through pattern queries in section 6.2.1.2. We then present the Cypher query language in section 6.2.1.3, which is a concrete language that makes it possible to query a graph database in the Neo4j graph database management system.

6.2.1.1. The graph data model

A graph database model is a model in which the data structures for the instances and/or the schema are modeled as a directed, possibly labeled graph or generalizations of the graph structure, where data manipulation is expressed by graph-oriented operations and type constructors [ANG 08]. Such a model makes it possible to naturally model networks of entities, where each node is described by a set of characteristics (for instance, a set of attributes) and...

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