This Week in Neo4j – Advent of Code, Using Neo4j with PySpark on Databricks, Dark Netflix Series Graph

Hello everyone,

It’s TWIN4j time. We’ll start with this week’s video, which is all about GoGM, an object graph mapper for Neo4j and the Go programming language.

Tomaz Bratanic does an extensive analysis of the ArXiv dataset, Lukas Böhres combines Neo4j and Pyspark, and a couple of people are trying out the Advent of Code puzzles.

And finally, Shyam Pratap Singh has built a graph based on Dark, the Netflix series.

Cheers, Mark and the Developer Relations team

This week’s featured community member is Alex F. Mills.

Alex F. Mills - This Week’s Featured Community Member

Alex F. Mills – This Week’s Featured Community Member

Alex is the Academic Director, Executive MBA in Healthcare Administration at the Zicklin School of Business in New York.

Alex studies design and control problems in service operations management. His research interests include healthcare operations, customer/patient type identification and imperfect information (triage), the impact of disruptions and resource limitations on system operations and recovery, and the impact of economic incentives on decision-making in healthcare.

Alex presented The Relationships that Define a Resilient Supply Chain at the Neo4j Connections: Graphs for Risk Mitigation in Supply Chains event earlier this year. In the talk, Alex goes through a variety of different supply chains, explaining their strengths and weaknesses, and showing why relationships are at the heart of this domain.

His talk was so popular that it’s been included in the Neo4j Connections: Best of 2020 Sessions that will run on 17th December 2020.

Introduction to GoGM: community OGM for Neo4j and Go

Our video this week is from Florent Biville’s live stream.

In this episode, Florent is joined by Erik Solender, the maintainer of GoGM, a Golang object graph mapper for Neo4j. Erik starts by explaining why he built GoGM, before showing how to model a simple domain using the library.

Florent also wrote a blog post a couple of weeks ago, in which he summarised some of his previous streams about Neo4j and Go.

Network analysis of ArXiv dataset to create a search and recommendation engine

In Tomaz Bratanic’s latest blog post, he builds a search and recommendation engine on top of the ArXiv dataset using graph data science techniques.

In the first half of the post, Tomaz takes us through various techniques for cleaning the data – converting text from Latex to UTF-8 encoding and removing duplicate entities. He then does some exploratory analysis of the data before using the GDS Library to analyse the author and citation networks.

Using Neo4j with PySpark on Databricks

Lukas Böhres shares an end-to-end workflow of setting up a fully interconnected pairing of Neo4j and Spark using the recently released Neo4j Connector for Apache Spark.

After deploying Neo4j and Spark instances in Azure, Lukas shows how to use the connector to both load data from Neo4j into Spark and write data from Spark to Neo4j.

Advent of Code, Spring Data Neo4j, Fraud and the GRANDstack

If you are a fan of Dark Netflix Series, here is a graph database for fun

Shyam Pratap Singh is a big fan of the Dark series on Netflix and has created a Neo4j graph based on the series.

After building the dataset, Shyam makes sense of the data using plain Cypher queries, the in-built shortest path algorithm, and clustering algorithms from the Graph Data Science Library.

Tweet of the Week

My favourite tweet this week was by David Bates:

Don’t forget to RT if you liked it too!