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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

Summary

In this chapter, we looked at building queries while applying filters. We have taken a look at filtering the data using node labels and relationship types, using relationship directions, the performance impact of using node labels when compared to relationship types for traversal, using WHERE clauses, WITH clauses, SKIP clauses, LIMIT clauses, and EXISTS clauses, and using regular expressions.

We looked at sorting the data using the ORDER BY clause with one value or multiple values in ascending order or in descending order and combining the ORDER BY clause with the WITH clause.

Finally, we looked at aggregating results using the COUNT, COLLECT, MIN, MAX, and AVG functions. Along with this, we also looked at combining the COUNT and COLLECT functions to perform some complex aggregations.

In the next chapter, we will take a look at using LIST expressions, working with the UNION clause. We will also take a look at using sub-queries using the CALL clause.

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