NoSQL data model : trends and challenges / edited by Olivier Pivert.
Contributor(s): Pivert, Olivier [editor.]
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Material type: 
BookSeries: Computer engineering series: databases and big data set ; volume 1.Publisher: London : Hoboken, NJ : ISTE Ltd ; John Wiley & Sons, Inc., 2018Copyright date: ©2018Description: 1 online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781119544135; 1119544130; 9781119528227; 1119528224.Subject(s): Non-relational databases | COMPUTERS / Database / General | Non-relational databasesGenre/Form: Electronic books.Additional physical formats: No titleDDC classification: 005.74 Online resources: Wiley Online Library Includes bibliographical references.
Cover; Half-Title Page; Title Page; Copyright Page; Contents; Foreword; Preface; 1. NoSQL Languages and Systems; 1.1. Introduction; 1.1.1. The rise of NoSQL systems and languages; 1.1.2. Overview of NoSQL concepts; 1.1.3. Current trends of French research in NoSQL languages; 1.2. Join implementations on top of MapReduce; 1.3. Models for NoSQL languages and systems; 1.4. New challenges for database research; 1.5. Bibliography; 2. Distributed SPARQL Query Processing: a Case Study with Apache Spark; 2.1. Introduction; 2.2. RDF and SPARQL; 2.2.1. RDF framework and data model
2.2.2. SPARQL query language2.3. SPARQL query processing; 2.3.1. SPARQL with and without RDF/Sentailment; 2.3.2. Query optimization; 2.3.3. Triple store systems; 2.4. SPARQL and MapReduce; 2.4.1. MapReduce-based SPARQL processing; 2.4.2. Related work; 2.5. SPARQL on Apache Spark; 2.5.1. Apache Spark; 2.5.2. SPARQL on Spark; 2.5.3. Experimental evaluation; 2.6. Bibliography; 3. Doing Web Data: from Dataset Recommendation to Data Linking; 3.1. Introduction; 3.1.1. The Semantic Web vision; 3.1.2. Linked data life cycles; 3.1.3. Chapter overview; 3.2. Datasets recommendation for data linking
3.2.1. Process definition3.2.2. Dataset recommendation for data linking based on a Semantic Web index; 3.2.3. Dataset recommendation for data linking based on socialnetworks; 3.2.4. Dataset recommendation for data linking based on domain specific keywords; 3.2.5. Dataset recommendation for data linking based on topicm odeling; 3.2.6. Dataset recommendation for data linking based on topic profiles; 3.2.7. Dataset recommendation for data linking based on intensional profiling; 3.2.8. Discussion on dataset recommendation approaches; 3.3. Challenges of linking data; 3.3.1. Value dimension
3.3.2. Ontological dimension3.3.3. Logical dimension; 3.4. Techniques applied to the data linking process; 3.4.1. Data linking techniques; 3.4.2. Discussion; 3.5. Conclusion; 3.6. Bibliography; 4. Big Data Integration in Cloud Environments: Requirements, Solutions and Challenges; 4.1. Introduction; 4.2. Big Data integration requirements in Cloud environments; 4.3. Automatic data store selection and discovery; 4.3.1. Introduction; 4.3.2. Model-based approaches; 4.3.3. Matching-oriented approaches; 4.3.4. Comparison; 4.4. Unique access for all data stores; 4.4.1. Introduction
4.4.2. ODBAPI: a unified REST API for relational and NoSQL data stores4.4.3. Other works; 4.4.4. Comparison; 4.5. Unified data model and query languages; 4.5.1. Introduction; 4.5.2. Data models of classical data integration approaches; 4.5.3. A global schema to unify the view over relational and NoSQL data stores; 4.5.4. Other works; 4.5.5. Comparison; 4.6. Query processing and optimization; 4.6.1. Introduction; 4.6.2. Federated query language approaches; 4.6.3. Integrated query language approaches; 4.6.4. Comparison; 4.7. Summary and open issues; 4.7.1. Summary; 4.7.2. Open issues
Description based on online resource; title from digital title page (viewed on November 01, 2018).
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