Last week I was helping out a user who was seeing lots of error messages in their application logs when connecting to Neo4j Aura. So I did like any good developer and I asked the all knowing all powerful google how to cleanse your Aura, and guess what it told me…
Question: Do you want to get Rich?
I’ll answer for you: “Yes!”
Follow along with this blog series and if it doesn’t make you rich, you can go back to your youtube videos, you can go back to watching Tiger King on Netflix, you can go back to your crappy life. Let’s continue.
Question: Are you poor? dumb? ugly? do you make bad decisions?
I’ll answer for you: “Yes!”.
If you were not poor, you would be on a yacht in Ibiza and not reading my blog. If you were not dumb you would be doing whatever it is smart people do, I wouldn’t know but I’m pretty sure it’s not reading my blog. If you were not ugly you would be in Paris or Milan murdering the runway instead of reading my blog. If you didn’t make bad decisions you wouldn’t have decided to read my blog which just made you feel sad about your life. See where I’m going with this?
In part one, we learned to listen to our users, in part two we began learning how to talk back. Before we go any further in to the stored procedure, how about we build a little front end to show off the work we’ve done so far on this proof of concept? That will also make things easier to test out and let us get into the mindset of the user. There are a ton of options here, lots of folks like Spring and Spring Boot. Others are more hipsters and into Micronaut. I am even more of a hipster and prefer to use Jooby, but it doesn’t really matter. We’ll be using Cypher, the Neo4j Drivers and the Stored Procedures we build along the way so technically you can do this in just about any language.
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In part one our this building a chatbot series, we figured out how to use OpenNLP to “hear” what a user is saying and figure out both their intent and any entities they may have mentioned. Today we’re going to learn how to use Neo4j to talk back… like an impudent child.
Last year eBay built a chatbot using Neo4j. Unfortunately we have grown so big I didn’t get a chance to work on that project and kinda feel left out. So I decided I’m going to build my own chatbot with Neo4j. As usual I’ve never done this before, have very little idea what I’m doing, have no team, and have barely any time to get this done. So with those disclaimers out of the way, let’s see what we can do.
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Is not that thing above. That’s a Chart, not a Graph. But anyway…Neo4j is designed to support the property graph model natively. There are a host of other technologies that can bolt-on a “graph layer” of some kind. However it doesn’t make them a graph database. It’s like adding a rear spoiler to a van, sure it may look cool… or ridiculous, but it won’t make it a race car. Don’t fall for it. If you need fast graph queries, use a real graph database. But today we won’t talk about that. Instead we’re going to talk about the real property graph…
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In the last blog post, we saw how we can use Neo4j to find the merchants where credit card fraud originated or was used for testing stolen data in order to prevent further fraudulent charges. It stemmed from a webinar on our amazing youtube channel with has hundreds of videos about graphs and Neo4j. We will continue diving in to the technical details by looking at how Neo4j can help you find Fraud Rings. The way this fraud works is that a large set of synthetic accounts are created and act like normal customers. Over time they request higher and higher levels of credit which they pay back on time. Then they all request the maximum credit they can get, take out the money, and disappear! Let’s find them before this happens.
It’s no secret that one of our hottest use cases lately has been Fraud Detection. A while back we did a webinar talking about some of the ways you could use Neo4j to fight fraud. Watch it, if you haven’t yet. Today I want to augment that webinar with some cypher queries. Let’s see how it works:
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How does the saying go? There are lies, damned lies, and benchmarks. I’ve already made my feelings about database vendor benchmarks known, but in case you missed it. They are complete fabrications. Never to be trusted, never ever. Never. But vendors love to do benchmarks, they love spreading fear, uncertainty and doubt instead of spending their time doing productive things like creating useful content that teaches people how to use their product. I wish I could just ignore this nonsense and focus on what really matters, like helping our customers to successful production rollouts, but alas, here we are.
Sometimes I contrast Neo4j against relational databases by saying Neo4j is more like a dynamic typed language, and relational databases are more like a static typed language. In Neo4j you don’t have Tables or table definitions, any property can be of any valid value (Java primitives, arrays of Java primitives as well as time and spatial types). Two nodes with the same Label can have completely different properties, and any key can be of any type for different nodes. So for example a User labeled node may have the “id” property be “xyz”, while the “id” property for a Location labeled node may be a spatial type… but another User labeled node may also have the “id” property be a number or an array of floats, or whatever. This kind of freedom can drive people crazy, but it can also be leveraged to make very dynamic applications easy.
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Max De Marzi 