Welcome to this week in Neo4j where we collect the most interesting things that have happened in the world of graph databases over the last 7 days.

If you’ve got something that you’d like to see featured in a future version let me know. I’m @markhneedham on Twitter or send an email to devrel@neo4j.com.


In last week’s online meetup Mesosphere’s Johannes Unterstein showed us how to get a Neo4j causal cluster up and running on DC/OS.



This was the culmination of several weeks’ effort where Johannes started with the Neo4j Docker image, figured out how to get it to play nicely with the Mesos ecosystem and created a Mesosphere Universe package so that users can easily create Neo4j clusters via the Marathon scheduler.

On top of this Johannes has been a part of the Neo4j community since 2013 and has organized several meetups as well as writing a Play Framework integration for Spring Data Neo4j.

On behalf of the Neo4j community I’d like to thank Johannes for all his efforts and I’m looking forward to your talk at GraphConnect Europe on 11th May 2017!

Using Graph Visualization to Explore Corruption in Egypt and FIFA


There were a couple of interesting posts showing how to use graph visualizations to explore two different types of corruption.

Lana Chan wrote What Do Big Data Paris and the Panama Papers Have In Common? In this post Lana shows how you can use the Tom Sawyer graph data visualization tool to explore the 2015 FIFA corruption scandal.

Explore everything that's happening in the Neo4j community for the week of 25 March 2017

Visualizing the Egypt corruption network

Noonpost, an interactive Arabic media website, explain how they used Linkurious for large-scale investigations in a project on Egypt’s corruption networks.

In the post, they explain how they were able to explore connections between the army and its affiliates across various influence networks including the health, food, and tourism sectors using a combination of Cypher queries and graph visualizations.

There’s lots of good stuff in both of these posts if you’re interested in data journalism.

If you’d like to do data journalism work using Neo4j but don’t know how, sign up for the Neo4j Data Journalism Accelerator Program and you’ll get the opportunity to work with engineers from Neo4j’s Developer Relations team to get your analysis up and running.

Visual Graph Modeling and Importing


Michael Hunger created a video showing how to sketch graph models and load them into Neo4j using Alistair Jonesarrows tool.



Will Lyon presented a webinar late last week where he showed how to model and import real-world datasets using Neo4j.

Will shows how to import data from Yelp using several different approaches:

    • apoc.load.json – a procedure from the APOC library that can import JSON data directly.
    • LOAD CSV – a Cypher command for importing CSV files. Works well up to ~10 million rows.
    • neo4j-import – a tool for importing large initial datasets.

Will also talks about Neo4j’s user-defined procedures and functions, and if you’re interested in creating your own ones we’ve created a couple of new pages on the Neo4j developer site to help you get started:

Emil in Forbes, Hiking Recommendations, Malware Clustering, and DC/OS


On the Podcast


This week Rik interviewed Alistair Jones about the Causal Clustering feature released in Neo4j 3.1 back in December.

They go through the history of clustering in Neo4j from the use of Zookeeper in the 1.8 series up to the current day where we’ve implemented a version of Diego Ongaro‘s Raft consensus protocol.

If you want to learn more, there’s also a video of Alistair presenting on this topic.

Next Week


So what’s there to look forward to in the world of graphs next week?

Tweet of the Week


My favorite tweet this week was by Jose Ramón Cajide who’s been analyzing Twitter networks using Neo4j in RStudio:

If you want to graph your own Twitter network you can try out the Neo4j Twitter Sandbox. Don’t forget to tweet your graph using the #Neo4j hashtag if you give it a try.

Enjoy your weekend, it’s finally spring – hoorah!

Cheers, Mark

 

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About the Author

Mark Needham, Developer Relations Engineer

Mark Needham is a graph advocate and developer relations engineer for Neo Technology, the company behind the Neo4j graph database.

As a developer relations engineer, Mark helps users embrace graph data and Neo4j, building sophisticated solutions to challenging data problems. Mark previously worked in engineering on the clustering team, helping to build the Causal Clustering feature released in Neo4j 3.1. Mark writes about his experiences of being a graphista on a popular blog at markhneedham.com. He tweets at @markhneedham.


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