Neo4j graph database is a high-performance database storage mode

Recently, I was studying the application of graph database Neo4j in network security, and I briefly searched and said that csv is a good way to enter the database, so I followed the tutorial on the official website to realize the data storage step by step.

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The tutorial on the official website [1] is particularly detailed, but in English, and I have reproduced it here, which is very simple.

If the CSV file does not have a header file, import it as follows:

LOAD CSV FROM 'file:///products.csv' AS row
WITH toInteger(row[0]) AS productId, row[1] AS productName, toFloat(row[2]) AS unitCost
MERGE (p:Product {productId: productId})
  SET p.productName = productName, p.unitCost = unitCost
RETURN count(p);           

If the CSV file has header files, the difference is that the column names must be the same, and the import method is as follows:

LOAD CSV WITH HEADERS FROM 'file:///orders.csv' AS row
WITH toInteger(row.orderID) AS orderId, datetime(replace(row.orderDate,' ','T')) AS orderDate, row.shipCountry AS country
MERGE (o:Order {orderId: orderId})
  SET o.orderDateTime = orderDate, o.shipCountry = country
RETURN count(o);           

In addition, indexing some IDs can speed up inbound performance:

CREATE CONSTRAINT UniqueProduct ON (p:Product) ASSERT p.id IS UNIQUE;
CREATE CONSTRAINT UniqueOrder ON (o:Order) ASSERT o.id IS UNIQUE;           

The above is the storage method of points, let's take a look at the storage method of the edge:

:auto USING PERIODIC COMMIT 500
LOAD CSV WITH HEADERS FROM 'file:///order-details.csv' AS row
WITH toInteger(row.productID) AS productId, toInteger(row.orderID) AS orderId, toInteger(row.quantity) AS quantityOrdered
MATCH (p:Product {productId: productId})
MATCH (o:Order {orderId: orderId})
MERGE (o)-[rel:CONTAINS {quantityOrdered: quantityOrdered}]->(p)
RETURN count(rel);           

At this time, it's done, and you can enjoy the renderings~

MATCH (o:Order)-[rel:CONTAINS]->(p:Product)
RETURN p, rel, o LIMIT 50;           

reference

1. ^NEO4J warehousing case https://neo4j.com/developer/desktop-csv-import/