Book Image

Graph Data Processing with Cypher

By : Ravindranatha Anthapu
Book Image

Graph Data Processing with Cypher

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)
1
Part 1: Cypher Introduction
4
Part 2: Working with Cypher
9
Part 3: Advanced Cypher Concepts

Conventions used

There are several text conventions used throughout this book.

Code in text: Indicates code words in the text, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “we are using the apoc procedure to add EncounterClass to an encounter node. Since we are trying to add labels dynamically, we have to use the apoc option.”

A block of code is set as follows:

CREATE (p {name: 'Tom'})
RETURN p

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold: “The Cypher query looks like this:

MATCH (d:Drug)<-[:HAS_DRUG]-()<-[:HAS_ENCOUNTER]-(p) 
WITH DISTINCT d, p
WITH d.description as drug, count(p) as patients
WHERE patients > 100
RETURN drug, patients

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “In particular, the addition of a new Encounter node and the HAS_END relationship are a bit different from how we approach data in the RDBMS world.”

Tips or important notes

Appear like this.