Neo4j 实战（三）-- Neo4j Loads CSV Files

前言：

这篇文章通过 NorthWind Graph 的例子熟悉并掌握 neo4j 导入 CSV 文件。

一、环境配置

在导入之前确保  neo4j.conf  中允许 CSV 导入。

打开 neo4j.conf:  $ vim neo4j.conf  

修改 dbms.security.allow_csv_import_from_file_urls=true 

二、数据准备

• products.csv (http://data.neo4j.com/northwind/products.csv)
• categories.csv (http://data.neo4j.com/northwind/categories.csv)
• suppliers.csv (http://data.neo4j.com/northwind/suppliers.csv)
• customers.csv(http://data.neo4j.com/northwind/customers.csv)
• orders.csv (http://data.neo4j.com/northwind/orders.csv)
• order-details.csv (http://data.neo4j.com/northwind/order-details.csv)

注意：从本地导入 CSV 文件时，需要将文件放在 import 文件夹下！

三、数据导入（本地）

1. 导入 products.csv 

//load products.csv
LOAD CSV WITH HEADERS FROM "file:///northwind/products.csv" AS row
CREATE (n:Product)
SET n = row,
n.unitPrice = toFloat(row.unitPrice),
n.unitsInStock = toInteger(row.unitsInStock), n.unitsOnOrder = toInteger(row.unitsOnOrder),
n.reorderLevel = toInteger(row.reorderLevel), n.discontinued = (row.discontinued <> "0")

 

2.导入 categories.csv

//load categories.csv
LOAD CSV WITH HEADERS FROM "file:///northwind/categories.csv" AS row
CREATE (n:Category)
SET n = row

 3. 导入 suppliers.csv

//load suppliers.csv
LOAD CSV WITH HEADERS FROM "file:///northwind/suppliers.csv" AS row
CREATE (n:Supplier)
SET n = row

4. 为产品等实体创建索引

给三类实体分别创建索引，方便后期提高查询效率。

//create indexes
CREATE INDEX ON :Product(productID)
CREATE INDEX ON :Category(categoryID)
CREATE INDEX ON :Supplier(supplierID)

5. 为产品等实体建立联系

为这三类实体建立联系，通过相同的 id 作为连接。

MATCH (p:Product),(c:Category)
WHERE p.categoryID = c.categoryID
CREATE (p)-[:PART_OF]->(c)

 商品和种类通过 categoryID 建立了联系

 

MATCH (p:Product),(s:Supplier)
WHERE p.supplierID = s.supplierID
CREATE (s)-[:SUPPLIES]->(p)

 商品和供应商通过 supplierID 建立了联系

 

6. 列出每个供应商提供的产品类别

MATCH (s:Supplier)-->(:Product)-->(c:Category)
RETURN s.companyName as Company, collect(distinct c.categoryName) as Categories

 每个食品供应商提供的产品种类表

 

7. 查找提供海产品("Seafood")的供应商

MATCH (c:Category {categoryName:"Seafood"})<--(:Product)<--(s:Supplier)
RETURN DISTINCT s.companyName as ProduceSuppliers

 8. 加载 customer.csv

LOAD CSV WITH HEADERS FROM "http://data.neo4j.com/northwind/orders.csv" AS row
CREATE (n:Order)
SET n = row

 9. 加载 order.csv

//load orders.csv
LOAD CSV WITH HEADERS FROM "file:///northwind/orders.csv" AS row
CREATE (n:Order)
SET n = row

 

10. 为订单等实体创建索引

//create indexes for customer and order
CREATE INDEX ON :Customer(customerID)
CREATE INDEX ON :Order(orderID)

11. 为订单等实体创建关系

//create relationships
MATCH (c:Customer),(o:Order)
WHERE c.customerID = o.customerID
CREATE (c)-[:PURCHASED]->(o)

12. 加载 order-details.csv

//load order-details.csv
LOAD CSV WITH HEADERS FROM "file:///northwind/order-details.csv" AS row
MATCH (p:Product), (o:Order)
WHERE p.productID = row.productID AND o.orderID = row.orderID
CREATE (o)-[details:ORDERS]->(p)
SET details = row,
details.quantity = toInteger(row.quantity)

 

四、数据查询

1. 列出订购了海产品(Seafood)的客户以及采购量

MATCH (cust:Customer)-[:PURCHASED]->(:Order)-[o:ORDERS]->(p:Product),
  (p)-[:PART_OF]->(c:Category {categoryName:"Seafood"})
RETURN DISTINCT cust.contactName as CustomerName, SUM(o.quantity) as TotalProductsPurchased

 2. 列出 "Thomas Hardy" 订购的产品及种类

match (cust:Customer{contactName:"Thomas Hardy"})-[:PURCHASED]->(:Order)-[ORDERS]->(p:Product),
    　(p)-[:PART_OF]->(c:Category)
   　　return p.productName as Product , c.categoryName as Category