Welcome to this week in Neo4j where we round up what’s been happening in the world of graph databases in the last 7 days.
This week we have DeepGL on Peer to Peer Network, Relational to Graph with APOC, Global Power Emissions Database, Graphs and AI, Agent Smith: A “top” application for Neo4j, and more!
Featured Community Member: Devansh Trivedi
This weeks featured community member is Devansh Trivedi, Data Scientist and Research Fellow.
Devansh Trivedi – This Week’s Featured Community Member
I came Devansh as a result of his prolific blogging about his experience using Neo4j as part of the 100 Days of Machine Learning challenge.
The challenge still has 70 days to go, so I like forward to seeing what else Devansh comes up with.
On behalf of the Neo4j community, thanks for all your work Devansh!
Extracting features from a peer to peer network using DeepGL
Tomaz Bratanic has written a blog post showing how to use the DeepGL graph embedding algorithm to extract features from a Peer to Peer network.
Tomaz then projects a cosine similarity graph based on those features and runs the Louvain algorithm to find communities of similar hosts.
Importing relational data into Neo4j using APOC
In the latest post of Michael Simons‘ series “From relational databases to databases with relations.” he explores different ways to import data into Neo4j.
Michael shows how to use the Neo4j ETL tool, and creates a custom import DSL, but settles on using APOC’s LOAD JDBC procedure because of the flexibility it provides.
Graphs and AI, Visualize Kubernetes cluster, Knowledge Graph Meetup
- Morgan Vawter, Chief Analytics Director at Caterpillar, has written an article on CIO Applications about AI and Graphs. Morgan observes that graphs can be used to build ontologies (shared structural conceptualizations of real world phenomena) and perform deduction (if the engine was removed, so was the piston because it is a subpart).
- Bajal wrote a blog post in which he shows how to use Neo4j to visualize a Kubernetes cluster.
- Dan Keeley wrote a blog post about a recent meetup on Knowledge Graphs presented by my colleague Petra Selmer.
- Bloodhound is a website of natural history collections.that uses Neo4j to store the scores between similarly structured people names.
Agent Smith: A “top” application for Neo4j
A couple of Fridays ago Nigel Small released Agent Smith 2.0, a “top” application for Neo4j. The application now watches transactions, rather than queries, which gives a more stable display of “things that are running”.
Up to 8 servers can now be displayed and Nigel’s also implemented a kill function, using
You can install Agent Smith by running the command:
pip install agentsmith
Poring over Power Plants: Global Power Emissions Database in Neo4j
Rik has written a blog post showing how to import and analyse a dataset containing Power Plants and their emissions into Neo4j.
After showing how to importing the data using the Neo4j browser’s multi-statement editor, Rik writes queries to find the biggest polluters, as well as most and least efficient plants.
GraphConnect Experience Report, Neo4j based CMDB, Spark, GraphX
- Arina Igumenshcheva wrote an experience report about GraphConnect NYC 2018, with a special focus on the data science talks from the conference.
- Dots is a janky, neo4j based CMDB glued together with PowerShell.
- Igor Bobriakov has written a blog post showing how to integrate Spark, GraphX, and Neo4j.
- Bartosz Konieczny has also written a post showing how to connect Spark to Neo4j using the Neo4j connector.
Tweet of the Week
My favourite tweet this week was by Noemi Derzsy:
Awesome workshop on Intro to #Neo4j Graph Database, where @lyonwj is sharing his knowledge with @wimlds attendees. Event organized by @WiMLDS_NYC. Thank you @nytimes for hosting us! pic.twitter.com/UvlooTyaEO— Noemi Derzsy (@NoemiDerzsy) October 23, 2018
Don’t forget to RT if you liked it too.
That’s all for this week. Have a great weekend!