Monthly Archives: September 2016

Delivering a Graph Based Search solution to slightly wrong data


When it comes to databases, having good clean data is always important. More so with Graphs which deal with concepts as nodes and their relationships between them. Inevitably, you will run into messy data and have to deal with it. In a lot of the projects our customers work on they are dealing with connecting multiple data sources to get to a “golden record” or single source of truth. A lofty goal, sometimes impossible to achieve, but we can use the relationships of the data to help us come close.

One option is to extract the features (or tags) of a composite object and see if any other object shares most of these features. If that is the case then they are possibly the same object and should be merged instead of creating a new record. A partial subgraph match is something akin to a recommendation engine in Neo4j and pretty trivial to write. Take a look back at a few old blog posts for ideas.
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Custom Importers


When it comes to getting data into Neo4j, you have a ton of options. You can use LOAD CSV from Cypher, you can use the Import Tool, you can use the JDBC connector in APOC, and possibly a few more options I’m forgetting. Some of these require the data to be in a specific format, others that you write a little custom cypher. These work very well most of the time, but sometimes you run into data in weird shapes and coming in from vendors who aren’t willing to change just for you. What do you do in that case? Well, you write a custom importer. I’m going to show you how by importing the Cities database from MaxMind.
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