Tag Archives: graph

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

5mysql

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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Our own Multi-Model Database – Part 3

shitty3

If you haven’t read part 1 and part 2 then do that first or you’ll have no clue what I’m doing, and I’d like to be the only one not knowing what I’m doing.

We’ve built the beginnings of this database but so far it’s just a library and for it to be a proper database we need to be able to talk to it. Following the Neo4j footsteps, we will wrap a web server around our database and see how it performs.

There are a ton of Java based frameworks and micro-frameworks out there. Not as bad as the Javascript folks, but that still leaves us with a lot of choices. So as any developer would do I turn to benchmarks done by other people of stuff that doesn’t apply to me, and you won’t believe what I found –scratch that, yes you will, I got benchmarks.
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OUR OWN MULTI-MODEL DATABASE – PART 2

shitty2

If you haven’t read part 1 then do that first or this won’t make sense, well nothing makes sense but this specially won’t.

So before going much further I decided to benchmark our new database and found that our addNode speed is phenomenal, but it was taking forever to create relationships. See some JMH benchmarks below:

Benchmark                                                           Mode  Cnt     Score     Error  Units
ChronicleGraphBenchmark.measureCreateEmptyNodes                    thrpt   10  1548.235 ± 556.615  ops/s
ChronicleGraphBenchmark.measureCreateEmptyNodesAndRelationships    thrpt   10     0.165 ±   0.007  ops/s

Each time I was creating 1000 users, so this test shows us we can create over a million empty nodes in one second. Yeah ChronicleMap is damn fast. But then when I tried to create 100 relationships for each user (100,000 total) it was taking forever (about 6 seconds). So I opened up YourKit and you won’t believe what I found out next (come on that’s some good clickbait).
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