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Graph Data Processing with Cypher

Graph Data Processing with Cypher

By : Ravindranatha Anthapu
4.7 (10)
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Graph Data Processing with Cypher

Graph Data Processing with Cypher

4.7 (10)
By: Ravindranatha Anthapu

Overview of this book

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.
Table of Contents (18 chapters)
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1
Part 1: Cypher Introduction
4
Part 2: Working with Cypher
9
Part 3: Advanced Cypher Concepts

Cypher

Nodes typically represent entities, such as concepts, events, places, and so on. Relationships connect the nodes that represent the context of how those two nodes are related. They can be considered as building blocks of the graph. The real strength of a property graph lies in its simplicity when it comes to representing and traversing patterns in graphs in an efficient manner.

Cypher is a query language based on graph traversal descriptions. These patterns are used to match the desired graph paths. When the matching pattern has been found, it can be used for further processing.

A simple pattern in Cypher is shown as follows:

(p:Person {name: "Tom"})–[:LIVES_IN]->
       (city:City {name: "Edison"})–[:PART_OF]->
       (country:Country {name: "United States"} )

The pattern here is self-explanatory and human-readable. A person named Tom lives in a city named Edison, which is a part of the country named the United States. You can see here that nouns represent the nodes and verbs represent the relationships.

We will take a deeper look at Cypher syntax in the coming chapters.

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