Tag Archives: graph

Work Order Management with Neo4j

I look terrible in a bikini (take my word for it) but I’d love me a Lamborghini. However, in order to afford nice things, we need to do as the song says and get to work…and we need to manage and prioritize that work somehow. Today, I’m going to show you how to build part of a work order management system with Neo4j.

I’m going to build an evented work order model. So let’s say our Order gets created, then based on what it is, pieces of Work need to happen. This work is performed by some Provider (whether internal or external) and that work can be broken down into Tasks that have dependencies on Events that have occurred. How would this look like in the graph? Glad you asked:
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Building a Boolean Logic Rules Engine in Neo4j

A boolean logic rules engine was the first project I did for Neo4j before I joined the company some 5 years ago. I was working for some start-up at the time but took a week off to play consultant. I had never built a rules engine before, but as far as I know ignorance has never stopped anyone from trying. Neo4j shipped me to the client site, and put me in a room with a projector and a white board where I live coded with an audience of developers staring at me, analyzing every keystroke and cringing at every typo and failed unit test. I forgot what sleep was, but managed to figure it out and I lost all sense of fear after that experience.

The data model chained together fact nodes with criss crossing relationships each chain containing the same path id property we followed until reaching an end node which triggered a rule. There were a few complications along the way and more complexity near the end for ordering and partial matches. The traversal ended up being some 40 lines of the craziest Gremlin code I ever wrote, but it worked. After the proof of concept, the project was rewritten using the Neo4j Java API because at the time only a handful of people could look at a 40 line Gremlin script and not shudder in horror. I think we’re up to two handfuls now.
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Finding Triplets with Neo4j

A user had an interesting Neo4j question on Stack Overflow the other day:

I have two types of nodes in my graph. One type is Testplan and the other is Tag. Testplans are tagged to Tags. I want most common pairs of Tags that share the same Testplans with a Tag having a specific name. I have been able to achieve the most common Tags sharing the same Testplan with one Tag, but getting confused when trying to do it for pairs of Tags.

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Flight Search with Neo4j

I think I am going to take the opportunity to explain why I love graphs in this blog post. I’m going to try to explain why looking at problems from the graph point of view opens you up to creative solutions and makes back-end development fun again. The context of our post is flight search, but our true mission is to figure out how to traverse a graph quickly and efficiently so we can apply our knowledge to other problems.

A long while back, I showed you different ways to model airline flight data. When it comes to modeling in graphs, the lesson to take away is that there is no right way. The optimal model is heavily dependent on the queries you want to ask. Just to prove the point, I’m going to show you yet another way to model the airline flight data that is truly optimized for flight search. If you recall, our last model looked like:
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Building a Twitter Clone with Neo4j – Part Seven

Alright, we’ve had enough back-end work on our Twitter Clone. Let’s switch gears and get to work on the front end. I’ve decided I’m going to use a Java micro framework for my front end, but if your language of choice is Ruby, Python, Go, or whatever, find an alternative library and follow along.

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Neo4j is faster than MySQL in performing recursive query

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A user on StackOverflow was wondering about the performance between Neo4j and MySQL for performing a recursive query. They started with Neo4j performing the query in 240 seconds. Then an optimized cypher query got them down to 40 seconds. Then I got them down to…
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Writing a Cypher Stored Procedure

luke-cage-jidenna

I’ve been so busy these last 6 months I just finally got around to watching Luke Cage on Netflix. The season 1 episode 5 intro is Jidenna performing “Long live the Chief” and it made me pause the series while I figured out who that was. I’m mostly a hard rock and heavy metal guy, but I do appreciate great pieces of lyrical work and this song made me take notice. Coincidently on the Neo4j Users Slack (get an invite) @sleo asked…
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Our own Multi-Model Database – Part 6

shitty6

Back in Part 2 we ran some JMH tests to see how many empty nodes we could create. Let’s try that test one more time, but adding some properties. Our nodes will have a username, an age and a weight randomly assigned. It’s not a long test, but just enough to give us a ballpark.
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Our own Multi-Model Database – Part 5

shitty5

In part 4 I promised metrics and a shell, so that’s what we’ll tackle today. We are lucky that the Metrics library can be plugged into Jooby without much effort… and double lucky that the Crash library can also be plugged into Jooby without much effort. This is what we are all about here because we’re a bunch of lazy, impatient developers who are ignorant of the limits of our capabilities and who would rather reuse open source code instead of falling victim to the “Not Invented Here” syndrome and do everything from scratch.
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Multi-Threading a Traversal

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What would you think if I ran out of time,
Would you stand up and walk out on me?
Lend me your eyes and I’ll write you a post
And I’ll try not to run out of memory.

Oh, I get by with a little help from my threads
Mm, I get high with a little help from my threads
Mm, gonna try with a little help from my threads

Today we are going to take a look at how to take a Neo4j traversal and split it up into lots of smaller traversals. I promise it will be electrifying.
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