Getting Started With The Graph Query Language Gql
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Getting Started With The Graph Query Language Gql
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Author : Ricky Sun
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-08-22
Getting Started With The Graph Query Language Gql written by Ricky Sun 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 2025-08-22 with Computers categories.
Learn how to build and query graph databases with this first comprehensive guide to ISO-standard GQL featuring 50+ hands-on examples and a real-world case study that will change the way you work with connected data Key Features Go beyond theory and apply key concepts and syntax through interactive tutorials and practical examples via the GQL Playground Leverage advanced features of GQL to manipulate graph data efficiently Explore GQL applications in data analytics and discover how to leverage graph knowledge in real-world scenarios Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGraph Query Language is becoming the go-to standard for graph databases, especially with its support for interconnected analytics and GenAI capabilities. This book comes from a team of industry veterans who know exactly how to break down the fundamental GQL concepts, graph terms, definitions, catalog systems, and everything that matters in actual work. You’ll get to grips with graph data types, value expressions, graph matching patterns, and modifying statements through practical GQL examples. With access to the GQL Playground via Ultipa Graph, you’ll get hands-on experience querying and manipulating graph data. Once you've got the basics down, you’ll tackle advanced GQL topics such as path modes, complex path matching patterns, shortest path queries, composite statements, session and transaction commands, and procedures. You’ll also learn to create extensions and understand the design of graph databases to solve industry issues. The authors cover techniques like property graphs to help you optimize your graph queries and offer insights into the future of GQL and graph technology. By the end of this book, you’ll confidently query and update graph data, run graph algorithms, and create visualizations. Plus, you’ll apply your learnings to a real-world use case of money flow analysis for assessing bank client behaviors and detecting transaction risks.What you will learn Experiment with GQL syntax on GQL Playground, including MATCH, RETURN, INSERT, UPDATE, and DELETE Work with operators, functions, and variables in an organized fashion Become familiar with complex topics such as varying path matching modes, repeated variables, shortest path, procedures, and transactions Enhance execution speed through indexing or caching systems Understand how to manage access control effectively Tackle real-world issues with a case study focused on money transaction analytics Who this book is for This book is for graph database developers, DBAs, programmers, data engineers, and analysts who want to learn the new graph database standard GQL. A basic understanding of graph and relational databases, data models, knowledge of SQL basics, and programming will make the content easy to grasp. While it is designed to be accessible even if you don’t have a background in graph theory, familiarity with concepts like nodes, edges, relationships, and the distinction between directed and undirected graphs will enhance your learning experience.
The Practitioner S Guide To Graph Data
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Author : Denise Gosnell
language : en
Publisher: O'Reilly Media
Release Date : 2020-03-20
The Practitioner S Guide To Graph Data written by Denise Gosnell and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-20 with Computers categories.
Graph data closes the gap between the way humans and computers view the world. While computers rely on static rows and columns of data, people navigate and reason about life through relationships. This practical guide demonstrates how graph data brings these two approaches together. By working with concepts from graph theory, database schema, distributed systems, and data analysis, you’ll arrive at a unique intersection known as graph thinking. Authors Denise Koessler Gosnell and Matthias Broecheler show data engineers, data scientists, and data analysts how to solve complex problems with graph databases. You’ll explore templates for building with graph technology, along with examples that demonstrate how teams think about graph data within an application. Build an example application architecture with relational and graph technologies Use graph technology to build a Customer 360 application, the most popular graph data pattern today Dive into hierarchical data and troubleshoot a new paradigm that comes from working with graph data Find paths in graph data and learn why your trust in different paths motivates and informs your preferences Use collaborative filtering to design a Netflix-inspired recommendation system
Hands On Graph Analytics With Neo4j
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Author : Estelle Scifo
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-21
Hands On Graph Analytics With Neo4j written by Estelle Scifo 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 2020-08-21 with Computers categories.
Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learning Key FeaturesGet up and running with graph analytics with the help of real-world examplesExplore various use cases such as fraud detection, graph-based search, and recommendation systemsGet to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scalingBook Description Neo4j is a graph database that includes plugins to run complex graph algorithms. The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You’ll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You’ll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You’ll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you’ll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you’ll get to grips with structuring a web application for production using Neo4j. By the end of this book, you’ll not only be able to harness the power of graphs to handle a broad range of problem areas, but you’ll also have learned how to use Neo4j efficiently to identify complex relationships in your data. What you will learnBecome well-versed with Neo4j graph database building blocks, nodes, and relationshipsDiscover how to create, update, and delete nodes and relationships using Cypher queryingUse graphs to improve web search and recommendationsUnderstand graph algorithms such as pathfinding, spatial search, centrality, and community detectionFind out different steps to integrate graphs in a normal machine learning pipelineFormulate a link prediction problem in the context of machine learningImplement graph embedding algorithms such as DeepWalk, and use them in Neo4j graphsWho this book is for This book is for data analysts, business analysts, graph analysts, and database developers looking to store and process graph data to reveal key data insights. This book will also appeal to data scientists who want to build intelligent graph applications catering to different domains. Some experience with Neo4j is required.
Big Data Infrastructure Technologies For Data Analytics
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Author : Yuri Demchenko
language : en
Publisher: Springer Nature
Release Date : 2024-10-25
Big Data Infrastructure Technologies For Data Analytics written by Yuri Demchenko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-25 with Computers categories.
This book provides a comprehensive overview and introduction to Big Data Infrastructure technologies, existing cloud-based platforms, and tools for Big Data processing and data analytics, combining both a conceptual approach in architecture design and a practical approach in technology selection and project implementation. Readers will learn the core functionality of major Big Data Infrastructure components and how they integrate to form a coherent solution with business benefits. Specific attention will be given to understanding and using the major Big Data platform Apache Hadoop ecosystem, its main functional components MapReduce, HBase, Hive, Pig, Spark and streaming analytics. The book includes topics related to enterprise and research data management and governance and explains modern approaches to cloud and Big Data security and compliance. The book covers two knowledge areas defined in the EDISON Data Science Framework (EDSF): Data Science Engineering and Data Management and Governance and can be used as a textbook for university courses or provide a basis for practitioners for further self-study and practical use of Big Data technologies and competent evaluation and implementation of practical projects in their organizations.
Spring Data
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Author : Mark Pollack
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-10-24
Spring Data written by Mark Pollack 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 2012-10-24 with Computers categories.
You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring Data makes it relatively easy to build applications across a wide range of new data access technologies such as NoSQL and Hadoop. Through several sample projects, you’ll learn how Spring Data provides a consistent programming model that retains NoSQL-specific features and capabilities, and helps you develop Hadoop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow. You’ll also discover the features Spring Data adds to Spring’s existing JPA and JDBC support for writing RDBMS-based data access layers. Learn about Spring’s template helper classes to simplify the use of database-specific functionality Explore Spring Data’s repository abstraction and advanced query functionality Use Spring Data with Redis (key/value store), HBase (column-family), MongoDB (document database), and Neo4j (graph database) Discover the GemFire distributed data grid solution Export Spring Data JPA-managed entities to the Web as RESTful web services Simplify the development of HBase applications, using a lightweight object-mapping framework Build example big-data pipelines with Spring Batch and Spring Integration
Cybersecurity Attacks Red Team Strategies
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Author : Johann Rehberger
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-03-31
Cybersecurity Attacks Red Team Strategies written by Johann Rehberger 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 2020-03-31 with Computers categories.
Develop your red team skills by learning essential foundational tactics, techniques, and procedures, and boost the overall security posture of your organization by leveraging the homefield advantage Key FeaturesBuild, manage, and measure an offensive red team programLeverage the homefield advantage to stay ahead of your adversariesUnderstand core adversarial tactics and techniques, and protect pentesters and pentesting assetsBook Description It's now more important than ever for organizations to be ready to detect and respond to security events and breaches. Preventive measures alone are not enough for dealing with adversaries. A well-rounded prevention, detection, and response program is required. This book will guide you through the stages of building a red team program, including strategies and homefield advantage opportunities to boost security. The book starts by guiding you through establishing, managing, and measuring a red team program, including effective ways for sharing results and findings to raise awareness. Gradually, you'll learn about progressive operations such as cryptocurrency mining, focused privacy testing, targeting telemetry, and even blue team tooling. Later, you'll discover knowledge graphs and how to build them, then become well-versed with basic to advanced techniques related to hunting for credentials, and learn to automate Microsoft Office and browsers to your advantage. Finally, you'll get to grips with protecting assets using decoys, auditing, and alerting with examples for major operating systems. By the end of this book, you'll have learned how to build, manage, and measure a red team program effectively and be well-versed with the fundamental operational techniques required to enhance your existing skills. What you will learnUnderstand the risks associated with security breachesImplement strategies for building an effective penetration testing teamMap out the homefield using knowledge graphsHunt credentials using indexing and other practical techniquesGain blue team tooling insights to enhance your red team skillsCommunicate results and influence decision makers with appropriate dataWho this book is for This is one of the few detailed cybersecurity books for penetration testers, cybersecurity analysts, security leaders and strategists, as well as red team members and chief information security officers (CISOs) looking to secure their organizations from adversaries. The program management part of this book will also be useful for beginners in the cybersecurity domain. To get the most out of this book, some penetration testing experience, and software engineering and debugging skills are necessary.
Graph Machine Learning
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Author : Aldo Marzullo
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-07-18
Graph Machine Learning written by Aldo Marzullo 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 2025-07-18 with Mathematics categories.
Enhance your data science skills with this updated edition featuring new chapters on LLMs, temporal graphs, and updated examples with modern frameworks, including PyTorch Geometric, and DGL Key Features Master new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL) Explore GML frameworks and their main characteristics Leverage LLMs for machine learning on graphs and learn about temporal learning Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGraph Machine Learning, Second Edition builds on its predecessor’s success, delivering the latest tools and techniques for this rapidly evolving field. From basic graph theory to advanced ML models, you’ll learn how to represent data as graphs to uncover hidden patterns and relationships, with practical implementation emphasized through refreshed code examples. This thoroughly updated edition replaces outdated examples with modern alternatives such as PyTorch and DGL, available on GitHub to support enhanced learning. The book also introduces new chapters on large language models and temporal graph learning, along with deeper insights into modern graph ML frameworks. Rather than serving as a step-by-step tutorial, it focuses on equipping you with fundamental problem-solving approaches that remain valuable even as specific technologies evolve. You will have a clear framework for assessing and selecting the right tools. By the end of this book, you’ll gain both a solid understanding of graph machine learning theory and the skills to apply it to real-world challenges.What you will learn Implement graph ML algorithms with examples in StellarGraph, PyTorch Geometric, and DGL Apply graph analysis to dynamic datasets using temporal graph ML Enhance NLP and text analytics with graph-based techniques Solve complex real-world problems with graph machine learning Build and scale graph-powered ML applications effectively Deploy and scale your application seamlessly Who this book is for This book is for data scientists, ML professionals, and graph specialists looking to deepen their knowledge of graph data analysis or expand their machine learning toolkit. Prior knowledge of Python and basic machine learning principles is recommended.
Advances In Databases And Information Systems
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Author : Joe Tekli
language : en
Publisher: Springer Nature
Release Date : 2024-09-01
Advances In Databases And Information Systems written by Joe Tekli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-01 with Computers categories.
This volume LNCS 14918 constitutes the refereed proceedings of 28th European Conference, ADBIS 2024, held in Bayonne, France, during August 28-31, 2024. The 15 full papers presented were carefully reviewed and selected from 43 submissions. The conference focuses on Algebra, Models, Schemata, Discovery and Data Analysis, Algorithms and Optimization, Access Methods and Query Processing, Advanced Architectures, Machine Learning, Large Language Models.
Scaling Python With Dask
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Author : Holden Karau
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-07-19
Scaling Python With Dask written by Holden Karau 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 2023-07-19 with Computers categories.
Modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing. But many scientific Python tools were not designed to leverage this parallelism. With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumPy, pandas, and scikit-learn. Authors Holden Karau and Mika Kimmins show you how to use Dask computations in local systems and then scale to the cloud for heavier workloads. This practical book explains why Dask is popular among industry experts and academics and is used by organizations that include Walmart, Capital One, Harvard Medical School, and NASA. With this book, you'll learn: What Dask is, where you can use it, and how it compares with other tools How to use Dask for batch data parallel processing Key distributed system concepts for working with Dask Methods for using Dask with higher-level APIs and building blocks How to work with integrated libraries such as scikit-learn, pandas, and PyTorch How to use Dask with GPUs
Big Data Architect S Handbook
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Author : Syed Muhammad Fahad Akhtar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-21
Big Data Architect S Handbook written by Syed Muhammad Fahad Akhtar 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 2018-06-21 with Computers categories.
A comprehensive end-to-end guide that gives hands-on practice in big data and Artificial Intelligence Key Features Learn to build and run a big data application with sample code Explore examples to implement activities that a big data architect performs Use Machine Learning and AI for structured and unstructured data Book Description The big data architects are the “masters” of data, and hold high value in today’s market. Handling big data, be it of good or bad quality, is not an easy task. The prime job for any big data architect is to build an end-to-end big data solution that integrates data from different sources and analyzes it to find useful, hidden insights. Big Data Architect’s Handbook takes you through developing a complete, end-to-end big data pipeline, which will lay the foundation for you and provide the necessary knowledge required to be an architect in big data. Right from understanding the design considerations to implementing a solid, efficient, and scalable data pipeline, this book walks you through all the essential aspects of big data. It also gives you an overview of how you can leverage the power of various big data tools such as Apache Hadoop and ElasticSearch in order to bring them together and build an efficient big data solution. By the end of this book, you will be able to build your own design system which integrates, maintains, visualizes, and monitors your data. In addition, you will have a smooth design flow in each process, putting insights in action. What you will learn Learn Hadoop Ecosystem and Apache projects Understand, compare NoSQL database and essential software architecture Cloud infrastructure design considerations for big data Explore application scenario of big data tools for daily activities Learn to analyze and visualize results to uncover valuable insights Build and run a big data application with sample code from end to end Apply Machine Learning and AI to perform big data intelligence Practice the daily activities performed by big data architects Who this book is for Big Data Architect’s Handbook is for you if you are an aspiring data professional, developer, or IT enthusiast who aims to be an all-round architect in big data. This book is your one-stop solution to enhance your knowledge and carry out easy to complex activities required to become a big data architect.