Tag Archives: technology

Importing the Hacker News Interest Graph

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Graphs are everywhere. Think about the computer networks that allow you to read this sentence, the road or train networks that get you to work, the social network that surrounds you and the interest graph that holds your attention. Everywhere you look, graphs. If you manage to look somewhere and you don’t see a graph, then you may be looking at an opportunity to build one. Today we are going to do just that. We are going to make use of the new Neo4j Import tool to build a graph of the things that interest Hacker News.
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One Direction Relationships in Neo4j

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In the Neo4j Property Graph model, every single Relationship must be Typed and Directed. This means they must have a specific name (FRIENDS, LIKES, FOLLOWS, etc) and have a Start Node and an End Node to show direction. What’s neat is that when you write your queries you can choose to ignore that. The following queries are all valid:

// Get all the people I follow 
MATCH (u1:Person)-[:FOLLOWS]->(u2:Person)
WHERE u1.username = "maxdemarzi"
RETURN u2.username

// Get all the people that I follow or follow me
MATCH (u1:Person)-[:FOLLOWS]-(u2:Person)
WHERE u1.username = "maxdemarzi"
RETURN u2.username

// Get all the people related to me 
MATCH (u1:Person)--(u2:Person)
WHERE u1.username = "maxdemarzi"
RETURN u2.username

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Giving Neo4j 2.2 a Workout

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Neo4j 2.2 is getting released any day now, so let’s put the Release Candidate through its paces with Gatling. Once we download and start it up, you’ll notice it wants us to authenticate.
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Kickstarting a Neo4j Video Series

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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Translating Cypher To Neo4j Java API 2.0

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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}))

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It’s over 9000! Neo4j on WebSockets

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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.

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Scaling Writes

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Most of the applications using Neo4j are read heavy and scale by getting more powerful servers or adding additional instances to the HA cluster. Writes however can be a little bit tricker. Before embarking on any of the following strategies it is best that the server is tuned. See the Linux Performance Guide for details. One strategy we’ve seen already is splitting the reads and writes to the cluster, so the writes only go to the Master. The brave can even change the push factor to zero and set a pull interval only in neo4j/conf/neo4j.properties:
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Knowledge Bases in Neo4j

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From the second we are born we are collecting a wealth of knowledge about the world. This knowledge is accumulated and interrelated inside our brains and it represents what we know. If we could export this knowledge and give it to a computer, it would look like ConceptNet. ConceptNet is a semantic network that…

…is built from nodes representing concepts, in the form of words or short phrases of natural language, and labeled relationships between them. These are the kinds of things computers need to know to search for information better, answer questions, and understand people’s goals.

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Extending Neo4j

One of the great things about Neo4j is how easy it is to extend it. You can extend Neo4j with Plugins and Unmanaged Extensions. Two great examples of plugins are the Gremlin Plugin (which lets you use the Gremlin library with Neo4j) and the Spatial Plugin (which lets you perform spatial operations like searching for data within specified regions or within a specified distance of a point of interest).

Plugins are meant to extend the capabilities of the database, nodes, or relationships. Unmanaged extensions are meant to let you do anything you want. This great power comes with great responsibility, so be careful what you do here. David Montag cooked up an unmanaged extension template for us to use on github so lets give it a whirl. We are going to clone the project, compile it, download Neo4j, configure Neo4j to use the extension, test the extension and tweak it a bit.
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