Querying Graphs
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Querying Graphs
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Author : Angela Bonifati
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Querying Graphs written by Angela Bonifati and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity. In this book, we present a concise unified view on the basic challenges which arise over the complete life cycle of formulating and processing queries on graph databases. To that purpose, we present all major concepts relevant to this life cycle, formulated in terms of a common and unifying ground: the property graph data model—the pre-dominant data model adopted by modern graph database systems. We aim especially to give a coherent and in-depth perspective on current graph querying and an outlook for future developments. Our presentation is self-contained, covering the relevant topics from: graph data models, graph query languages and graph query specification, graph constraints, and graph query processing. We conclude by indicating major open research challenges towards the next generation of graph data management systems.
Human Interaction With Graphs
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Author : Sourav S. Bhowmick
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2018-08-08
Human Interaction With Graphs written by Sourav S. Bhowmick and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-08 with Computers categories.
Interacting with graphs using queries has emerged as an important research problem for real-world applications that center on large graph data. Given the syntactic complexity of graph query languages (e.g., SPARQL, Cypher), visual graph query interfaces make it easy for non-programmers to query such graph data repositories. In this book, we present recent developments in the emerging area of visual graph querying paradigm that bridges traditional graph querying with human computer interaction (HCI). Specifically, we focus on techniques that emphasize deep integration between the visual graph query interface and the underlying graph query engine. We discuss various strategies and guidance for constructing graph queries visually, interleaving processing of graph queries and visual actions, visual exploration of graph query results, and automated performance study of visual graph querying frameworks. In addition, this book highlights open problems and new research directions. In summary, in this book, we review and summarize the research thus far into the integration of HCI and graph querying to facilitate user-friendly interaction with graph-structured data, giving researchers a snapshot of the current state of the art in this topic, and future research directions.
Human Interaction With Graphs
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Author : Sourav S. Bhowmick
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Human Interaction With Graphs written by Sourav S. Bhowmick and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Interacting with graphs using queries has emerged as an important research problem for real-world applications that center on large graph data. Given the syntactic complexity of graph query languages (e.g., SPARQL, Cypher), visual graph query interfaces make it easy for non-programmers to query such graph data repositories. In this book, we present recent developments in the emerging area of visual graph querying paradigm that bridges traditional graph querying with human computer interaction (HCI). Specifically, we focus on techniques that emphasize deep integration between the visual graph query interface and the underlying graph query engine. We discuss various strategies and guidance for constructing graph queries visually, interleaving processing of graph queries and visual actions, visual exploration of graph query results, and automated performance study of visual graph querying frameworks. In addition, this book highlights open problems and new research directions. In summary, in this book, we review and summarize the research thus far into the integration of HCI and graph querying to facilitate user-friendly interaction with graph-structured data, giving researchers a snapshot of the current state of the art in this topic, and future research directions.
Querying Graph Structured Data
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Author : Lei Yang
language : en
Publisher:
Release Date : 2015
Querying Graph Structured Data written by Lei Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computer science categories.
With the emergence of bioinformatics and social science applications, a large amount of data can be represented as graphs. Thus, there is an increasing interest in developing diverse graph algorithms that operate on large graphs. In this thesis, we discuss diverse graph problems including the pedigree computation problem in the bioinformatics field and a general purpose graph query problem -- graph pattern matching problem, which can be applied to social network. First, a pedigree is a diagram of family relationships, and it is often used to determine the mode of inheritance (dominant, recessive, etc.) of genetic diseases. The pedigree computation problem studies the evaluation of the inbreeding coefficient of a given individual using Compact Path Encoding (CPE), which is a new compact path encoding scheme for large pedigrees. We design a set of efficient algorithms for identifying paths based on CPE. In addition, we present time and space complexity analysis, and also manifest the efficiency of our method for evaluating inbreeding coefficients as compared to previous methods by experimental results using pedigree graphs with real and synthetic data. Both theoretical and experimental results demonstrate that our method is more scalable and efficient than previous methods in terms of time and space requirements. Second, querying large data graphs efficiently with a flexible query pattern is an important research problem due to a wide range of applications with large graph structured data. As the sizes of data graphs become increasingly larger, more efficient techniques are needed to achieve better query performance. In this part, we focus on designing techniques to find all the matches for a user-provided query pattern in a large data graph (graph pattern matching problem) based on subgraph isomorphism. The query pattern used in this work extends the traditional one by supporting paths with distance constraints. To evaluate such query patterns, we propose a hybrid inverted index, and an efficient query evaluation algorithm with join order optimization -- JAGUAR (standing for join-based graph pattern querying algorithm). The scalability and efficiency of our proposed methods are demonstrated by detailed experiments on a set of synthetic and real datasets.Moving forward, we improve the scalability of our approach by adapting it to a distributed environment. The extension includes a distributed version of VEJoint & Hubs Index as well as the construction algorithms, a distributed computation model which is customized for the graph pattern matching problem and the new query evaluation algorithm based on the model. As an important feature of our distributed computation model, we significantly reduced the network communication during the query evaluation procedure, which largely improves the query performance. At last, we test the query performance of our distributed algorithm using data graphs as large as 100 million of edges with a cluster of up-to 16 machines. The experimental results demonstrate that with only 16 machines, our algorithm can evaluate the query pattern in tens of milliseconds.
Graph Data Management
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Author : George Fletcher
language : en
Publisher: Springer
Release Date : 2018-10-31
Graph Data Management written by George Fletcher and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.
This book presents a comprehensive overview of fundamental issues and recent advances in graph data management. Its aim is to provide beginning researchers in the area of graph data management, or in fields that require graph data management, an overview of the latest developments in this area, both in applied and in fundamental subdomains. The topics covered range from a general introduction to graph data management, to more specialized topics like graph visualization, flexible queries of graph data, parallel processing, and benchmarking. The book will help researchers put their work in perspective and show them which types of tools, techniques and technologies are available, which ones could best suit their needs, and where there are still open issues and future research directions. The chapters are contributed by leading experts in the relevant areas, presenting a coherent overview of the state of the art in the field. Readers should have a basic knowledge of data management techniques as they are taught in computer science MSc programs.
Graph Data Processing With Cypher
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Author : Ravindranatha Anthapu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-12-16
Graph Data Processing With Cypher written by Ravindranatha Anthapu and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-16 with Computers categories.
Get acquainted with Cypher in a guided manner quickly and learn how to query the graph databases with efficient and performant queries Key Features Work with Cypher syntax and semantics while building graph traversal queries Get up and running with advanced Cypher concepts like List, Maps, OPTIONAL MATCH Master best practices in writing effective queries leveraging data modeling and patterns Book DescriptionWhile it is easy to learn and understand the Cypher declarative language for querying graph databases, it can be very difficult to master it. As graph databases are becoming more mainstream, there is a dearth of content and guidance for developers to leverage database capabilities fully. This book fills the information gap by describing graph traversal patterns in a simple and readable way. This book provides a guided tour of Cypher from understanding the syntax, building a graph data model, and loading the data into graphs to building queries and profiling the queries for best performance. It introduces APOC utilities that can augment Cypher queries to build complex queries. You’ll also be introduced to visualization tools such as Bloom to get the most out of the graph when presenting the results to the end users. After having worked through this book, you’ll have become a seasoned Cypher query developer with a good understanding of the query language and how to use it for the best performance.What you will learn Write Cypher queries from basic to advanced level Map the source data to the graph data model in an iterative fashion Load the data into a graph using LOAD CSV, APOC, and client drivers Map the business questions to graph queries effectively Identify query performance issues and fix them Extend capabilities of Cypher using APOC utilities Work with graph visualization tools like Bloom and Browser Who this book is for This book is targeted at Database Administrator, Database Developers, Graph Database Developers, and Graph Database Architects. This book will also help someone migrate from a DBA role to a graph data engineer or data scientist If you are working with graph databases and need to learn Cypher, or are a basic Cypher developer who wants to get better at data modeling and tuning queries to build performant Cypher queries, then this is the book for you.
Modeling And Querying Graph Data
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Author : Hong Yang
language : en
Publisher:
Release Date : 2009
Modeling And Querying Graph Data written by Hong Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computer interfaces categories.
Databases are used in many applications, spanning virtually the entire range of data processing services industry. The data in many database applications can be most naturally represented in the form of a graph structure consisting of various types of nodes and edges with several properties. These graph data can be classified into four categories: social networks describing the relationships between individual person and/or groups of people (e.g. genealogy, network of co authorship among academics, etc); information networks in which the structure of the network reflects the structure of the information stored in the nodes (e.g. citation network among academic papers, etc); geographic networks, providing geographic information about public transport systems, airline routes, etc; and biological networks (e.g. biochemical networks, neuron network, etc). In order to analyze such networks and obtain desired information that users are interested in, some typical queries must be conducted. It can be seen that many of the query patterns are across multiple categories described above, such as finding nodes with certain properties in a path or graph, finding the distance between nodes, finding sub-graphs, paths enumeration, etc. However, the classical query languages like SQL, OQL are inept dealing with these types of queries needed to be performed in the above applications. Therefore, a data model that can effectively represent the graph objects and their properties, and a query language which empowers users to answer queries across multiple categories are needed. In this research work, a graph data model and a query language are proposed to resolve the issues existing in the current database applications. The proposed graph data model is an object-oriented graph data model which aims to represent the graph objects and their properties for various applications. The graph query language empowers users to query graph objects and their properties in a graph with specified conditions. The capability to specify the relationships among the entities composing the queried sub-graph makes the language more flexible than others.
Graph Databases
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Author : Ian Robinson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-06-10
Graph Databases written by Ian Robinson and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-10 with Computers categories.
Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information
Graph Databases
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Author : Ian Robinson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2015-06-10
Graph Databases written by Ian Robinson and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-10 with Computers categories.
Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information
Qp Subdue
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Author : Ankur Goyal
language : en
Publisher:
Release Date : 2016
Qp Subdue written by Ankur Goyal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Graphs have become one of the preferred ways to store structured data for various applications such as social network graphs, complex molecular structure, etc. Proliferation of graph databases has resulted in a growing need for effective querying methods to retrieve desired information. Querying has been widely studied in relational databases where the query optimizer finds a sequence of query execution steps (or plans) for e cient execution of the given query. Until now, most of the work on graph databases has concentrated on mining. For querying graph databases, users have to either learn a graph query language for posing their queries or use provided customized searches of specific substructures. Hence, there is a clear need for posing queries using graphs, consider alternative plans, and select a plan that can be pro- cessed efficiently on the graph database. In this thesis, we propose an approach to generate plans from a query using a cost-based approach that is tailored to the characteristics of the graph database. We collect metadata pertaining to the graph database and use cost estimates to evaluate the cost of execution of each plan. We use a branch and bound algorithm to limit the state space generated for identifying a good plan. Extensive experiments on different types of queries over two graph databases (IMDB and DBLP) are performed to validate our approach. Subdue a graph mining algorithm has been modified to process a query plan instead of performing mining.