Importing CSV to neo4J

CSV is a file of comma-separated values, often viewed in Excel or some other spreadsheet tool. There can be other types of values as the delimiter, but the most standard is the comma. Many systems and processes today already convert their data into CSV format for file outputs to other systems, human-friendly reports, and other needs. It is a standard file format that humans and systems are already familiar with using and handling.

Ways to Import CSV Files

LOAD CSV Cypher command: this command is a great starting point and handles small- to medium-sized data sets (up to 10 million records).

neo4j-admin bulk import tool: command line tool useful for straightforward loading of large data sets.

Kettle import tool: maps and executes steps for the data process flow and works well for very large data sets, especially if developers are already familiar with using this tool.

LOAD CSV command with Cypher

Supports loading / ingesting CSV data from a URI

Directly maps input data into complex graph/domain structure

Handles data conversion

Supports complex computations

Creates or merges entities, relationships, and structure

LOAD CSV can handle local and remote files, and there is some syntax associated with each. This can be an easy thing to miss and end up with an access error, so we will try to clarify the rules here.

Local files are referenced with a file:/// prefix before the file name. Neo4j security has a default setting that local files can only be read from the Neo4j import directory, which is different based on your operating system.

recommend putting files in Neo4j’s import directory, as it keeps the environment secure

//Example 1 - file directly placed in import directory (import/data.csv)

LOAD CSV FROM "file:///data.csv"

//Example 2 - file placed in subdirectory within import directory (import/northwind/customers.csv)

LOAD CSV FROM "file:///northwind/customers.csv"

mportant Tips for LOAD CSV

There are a few things to keep in mind with LOAD CSV and a few helpful tips for handling the variety of data scenarios you are likely to encounter.

Newer versions of Neo4j will most likely be faster due to continued optimization.

All data from the CSV file is read as a string, so you need to use toInteger(), toFloat(), split() or similar functions to convert values.

Check your Cypher import statement for typos. Labels, property names, relationship-types, and variables are case-sensitive.

The cleaner the data, the easier the load. Try to handle complex cleanup/manipulation before load.

References:

https://neo4j.com/developer/guide-import-csv/