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Writing a Cypher Stored Procedure

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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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Scaling Cypher Writes

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Let’s talk about writes, baby. Let’s talk about you and me. Let’s talk about all the good things. And the bad things that may be. Let’s talk about writes, and indexing and batching, and transactions in Neo4j. Let’s start with my environment. A 3 year old MacBook Pro (dying to get the new ones… once they finally come out) running a 4 core 2.3 GHz Intel Core i7 that is hyper-threading and pretending to have 8. An Apple SM256E SSD that is about average as far as SSDs go. So definitely not a production grade server, so bear that in mind.
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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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Translating Cypher to Java

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The expressive power of Cypher is already awesome and getting better with the Neo4j 2.0 release. Let’s take a step back from the bleeding edge and see Cypher in 1.9.4 and how it can be translated into Java. First a simple example where we look up a User node by an index and return a list of usernames belonging to the people who are that user’s friends:

START me = node:Users(username='maxdemarzi')
MATCH me -[:FRIENDS]-> people
RETURN people.username

The Cypher statement expresses what I want even better than my botched explanation in English. So how would we do this in the Neo4j Java API?
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Facebook Graph Search with Cypher and Neo4j

Update: Facebook has disabled this application

Your app is replicating core Facebook functionality.

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Facebook Graph Search has given the Graph Database community a simpler way to explain what it is we do and why it matters. I wanted to drive the point home by building a proof of concept of how you could do this with Neo4j. However, I don’t have six months or much experience with NLP (natural language processing). What I do have is Cypher. Cypher is Neo4j’s graph language and it makes it easy to express what we are looking for in the graph. I needed a way to take “natural language” and create Cypher from it. This was going to be a problem.
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Personalization with Cypher

You hopefully have seen a TV commercial from “The Man Your Man Could Smell Like” marketing campaign put on by Old Spice, and you may have seen some of the over 100 videos Isaiah Mustafa appeared in responding to comments made on Twitter. This is a great example of personalization, and today you’ll learn how you can bring some personalization to your application, and you won’t need muscles or a horse.

We’re going to dust off the Neoflix project from the beginning of the year and add a few features. It has been updated to work on Neo4j version 1.7 and allows searching for movies that have a quote. Thanks to Jenn Alons and Vince Cima for the bug fixes during WindyCityDB.
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Visualizing a Network with Cypher and D3.js

We’ve seen some pretty nice visualizations of nodes and their immediate neighbors, but we want to be able to visualize more. So we’re going to prepare a 200 node network, use Cypher to extract the data we want and visualize it with D3.js.
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Cypher with Neography

Cypher is the query language of Neo4j, and as promised I’ll show you how you can use it to implement friend recommendations as well as degrees of separation.

We can send any cypher query to Neo4j via the REST API and neography using the execute_query command. Let’s implement suggestions_for so it sends a cypher query to the server:

def suggestions_for(node)
  node_id = node["self"].split('/').last.to_i
  @neo.execute_query("START me = node({node_id})
                      MATCH (me)-[:friends]->(friend)-[:friends]->(foaf)
                      RETURN foaf.name", {:node_id => node_id})["data"]
end

puts "Johnathan should become friends with #{suggestions_for(johnathan).join(', ')}"

# RESULT
# Johnathan should become friends with Mary, Phil

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Using a Cuckoo Filter for Unique Relationships

We often see a pattern in Neo4j applications where a user wants to create one and only one relationship between two nodes. For example a User follows another User on a social network. We don’t want to accidentally create a second follows relationship because that may create errors such as duplicate entries on their feed, or errors unfollowing or blocking them, or even skew recommendation algorithms. Also it is just plain wasteful, and while an occasional duplicate relationship won’t be a big deal, millions of them could.

So how do we deal with this?
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Building a Twitter Clone with Neo4j – Part Six

We are getting close to wrapping up the back-end API for our Twitter clone, so thank you for sticking with this awfully long series since the beginning. One of the big community features of Twitter is the Trending Hashtags. It lets users know what is being talked about even if the people a user follows aren’t talking about it. It’s kind of weird in that way since part of the point of Twitter is following just a few hundred or thousand people to reduce the noise, and here we are bringing noise back in to our feed. Regardless, this is actually pretty easy to implement, so let’s have a crack at it.
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