Graph Data Processing with Cypher
Language: English
Published by Packt Publishing Limited, GB, 2022
- Softcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
£ 43.67
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Add to basketItem description from seller
Cypher is a great language to express graph traversals, but it still requires a bit of change in the thinking process to write performant cypher queries. This book will help to get the best out of neo4j using cypher language and its capabilities.
Seller Inventory # LU-9781804611074
- Title
- Graph Data Processing with Cypher
- Author
- Ravindranatha Anthapu
- Publisher
- Packt Publishing Limited, GB
- Publication year
- 2022
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1804611077
- ISBN 13
- 9781804611074
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 Description
While 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.
Table of Contents
- Introduction to Neo4j and Cypher
- Components of Cypher
- Loading Data with Cypher
- Querying Graph
- Filtering, Sorting, and Aggregations
- List Expressions, UNION, and Subqueries
- Working with Lists and Maps
- Advanced Query Patterns
- Query Tuning
- Using APOC Utilities
- Cypher Ecosystem
- Tips and Tricks
"Synopsis" may belong to another edition of this title.
About the Author
Ravindranatha Anthapu has more than 25 years of experience in working with W3C standards or building cutting-edge technologies like integrating speech with mobile applications in the 2000s. He is a technology enthusiast who worked from operating system device drivers to writing compilers for C language to modern web technologies, transitioning seamlessly and bringing experience from each of these domains and technologies to deliver successful solutions today. As a Principal Consultant at Neo4j today, Ravindranatha works with large enterprise customers to make sure they are able to leverage graph technologies effectively across various domains.
"About the title" may belong to another edition of this title.
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