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Learning Neo4j : run blazingly fast queries on complex graph datasets with the power of the Neo4j graph database /
This book is for developers who want an alternative way to store and process data within their applications. No previous graph database experience is required; however, some basic database knowledge will help you understand the concepts more easily.
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
[2014]
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| Colección: | Community experience distilled.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Graphs and Graph Theory
- an Introduction; Introduction to and history of graphs; Definition and usage of graph theory; Social studies; Biological studies; Computer science; Flow problems; Route problems; Web search; Test questions; Summary; Chapter 2: Graph Databases
- Overview; Background; Navigational databases; Relational databases; NoSQL databases; Key-Value stores; Column-Family stores; Document stores; Graph databases; The Property Graph model of graph databases.
- Node labelsRelationship types; Why (or why not) graph databases; Why use a graph database?; Complex queries; In-the-clickstream queries on live data; Path finding queries; Why not use a graph database, and what to use instead; Large, set-oriented queries; Graph global operations; Simple, aggregate-oriented queries; Test questions; Summary; Chapter 3: Getting Started with Neo4j; Neo4j
- key concepts and characteristics; Built for graphs, from the ground up; Transactional, ACID-compliant database; Made for Online Transaction Processing; Designed for scalability.
- A declarative query language
- CypherSweet spot use cases of Neo4j; Complex, join-intensive queries; Path finding queries; Committed to open source; The features; The support; The license conditions; Installing Neo4j; Installing Neo4j on Windows; Installing Neo4j on Mac or Linux; Using Neo4j in a cloud environment; Test Questions; Summary; Chapter 4: Modeling Data for Neo4j; The four fundamental data constructs; How to start modeling for graph databases; What we know
- ER diagrams and relational schemas; Introducing complexity through join tables.
- A graph model
- a simple, high-fidelity model of realityGraph modeling
- best practices and pitfalls; Graph modeling best practices; Design for query-ability; Align relationships with use cases; Look for n-ary relationships; Granulate nodes; Use in-graph indexes when appropriate; Graph database modeling pitfalls; Using ""rich"" properties; Node representing multiple concepts; Unconnected graphs; The dense node pattern; Test questions; Summary; Chapter 5: Importing Data into Neo4j; Alternative approaches to importing data into Neo4j; Know your import problem
- choose your tooling.
- Importing small(ish) datasetsImporting data using spreadsheets; Importing using Neo4j-shell-tools; Importing using Load CSV; Scaling the import; Questions and answers; Summary; Chapter 6: Use Case Example
- Recommendations; Recommender systems dissected; Using a graph model for recommendations; Specific query examples for recommendations; Recommendations based on product purchases; Recommendations based on brand loyalty; Recommendations based on social ties; Bringing it all together
- compound recommendations; Business variations on recommendations; Fraud detection systems.