Ron Burgundy (in Anchorman) gets Hungry
The “News Feed” is a core feature of social networks like Twitter, Facebook, or Vine (RIP). Let’s take a look at how we could model and implement this in Neo4j. Our social network needs Users (otherwise it would be kinda empty) that FOLLOW each other (otherwise it would not be very social). Those users need to POST some Messages (otherwise it would be boring). Here is our first attempt at a model (using Arrows):
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A few folks have come to us recently with the need to trace lineages of nodes of variable depth many hops away. You can run into this need if you are looking at the ancestries of living things, tracing data as it flows through an ETL, large network connectivity maps, etc. These types of queries tend to be murder on relational databases because of the massive recursive joins they have to deal with. Let’s give them a try in Neo4j.
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For the most part, I hate competitive benchmarks. The vendor who publishes them always seems to come out on top regardless. The numbers are always amazing, but once you start digging in a little bit you start to see faults in what is actually being measured and it never applies to real world workloads. For example you have Cassandra claiming 1 Million writes per second on 300 servers. Then Aerospike claiming 1 Million writes per second on 50 servers. MongoDB claiming almost 32k writes per second on a single server, but claiming Cassandra can only do 6k w/s and Couch can only do 1.2k w/s on a single server… Then ScyllaDB has almost 2 Million writes per second on 3 servers blowing everybody away.
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Actor Leonardo DiCaprio as Frank Abagnale in the Steven Spielberg movie “Catch Me If You Can”
If you’ve come to any of the Neo4j Data Modeling classes I’ve taught, you’ve must have heard me say “your model depends on both your data and your queries” about a million times. Let us take a closer dive into what this means by looking at how one might model airline flight data in Neo4j.
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I’ve been creating both unit tests and integration tests for Neo4j Unmanaged Extensions for far too long. The Neo4j Testing Harness was introduced in version 2.1.6 to simplify our lives and just do integration tests. Let’s try it on and see just how awesome we look. First thing we need to do is add the dependency to our project:
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A while ago, I showed you a way to scale Neo4j writes using RabbitMQ. Which was kinda cool, but some of you asked me for a different solution that didn’t involve adding yet another software component to the stack.
Turns out we can do this in just Neo4j using a little help from the Guava library. The solution involved a background service running that holds the writes in a queue, and every once in a while (like say every second) commits those writes in one transaction.
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Learn how to build high performance @neo4j applications with this video training course.
I’m on Kickstarter to ask for your help in order to create a set of videos to teach you how to build high performance Neo4j applications. I am going to capture the lessons I’ve learned over the past 4 years working with graph databases and share them with you.
These videos will teach you everything you need to know about building high performance applications using Neo4j.
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About 6 months ago we looked at how to translate a few lines of Cypher in to way too much Java code in version 1.9.x. Since then Cypher has changed and I suck a little less at Java, so I wanted to share a few different ways to translate one into the other just in case you stuck in a mid-eighties time warp and are paid by the number of lines of code you write per hour.
But first, lemme take a #Selfie let’s make some data. Michael Hunger has a series of blog posts on getting and creating data in Neo4j, we’ll steal borrow his ideas. Let’s create 100k nodes:
WITH ["Jennifer","Michelle","Tanya","Julie","Christie","Sophie","Amanda","Khloe","Sarah","Kaylee"] AS names
FOREACH (r IN range(0,100000) | CREATE (:User {username:names[r % size(names)]+r}))
Just because you can, doesn’t mean you should. However sometimes it can be comforting to know how. I am going to show you how to run Neo4j Embedded and Neo4j Server at the same time…and an Unmanaged Extension inside that Neo4j Server. There aren’t any real good reasons why you’d want to do this, but it’s April Fools, so here we go.
In the last blog post we managed to run Neo4j at Ludicrous Speed over http using Undertow and get to about 8000 requests per second. If we needed more speed we can scale up the server or we can scale out to multiple servers by switching out the GraphDatabaseFactory and using the HighlyAvailableGraphDatabaseFactory class instead in Neo4j Enterprise Edition.
But can we go faster on a single server without new hardware? Well… yes, if we’re willing to drop http and switch to Web Sockets.
Max De Marzi 