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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

Reviewing plan operators

We will take a look at a few important operators that we will encounter most often while tuning queries.

These operators impact query performance the most and are listed as follows:

  • AllNodesScan: This means the database is looking at all the nodes. Most often than not, this means the user forgot to provide a label. There are scenarios where this might be the intention. Most users when they are beginning with Cypher add the label name but forget to add ":" before the label. An example looks like this:
    MATCH (Drug {code: '1234'} RETURN *

We might have thought we provided the label name, but since we don’t have ":" before the label, it will be treated as a variable, and we will see all nodes are being looked at.

  • CartesianProduct: This is a scenario when we have multiple MATCH statements without the WITH clause between them. A sample of such a scenario looks like this:
    MATCH (p:Patient)
    MATCH (d:Drug)
    RETURN...

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