4.2、从RDBMS向Neo4j导数据【专题四：数据处理】

本文主要是介绍4.2、从RDBMS向Neo4j导数据【专题四：数据处理】，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

1、目标

　　介绍将从PostgreSQL（RDBMS）导出的数据导入Neo4j（GraphDB）,即将关系数据库模式建模，使之形成图。
　　预备知识：熟悉图模型并安装neo4j服务

2、导RDBMS数据到Neo4j

2.1、RDBMS数据集

　　用到的数据集是NorthWind dataset（点击下载），该数据库的E-R图如下：

2.2、构建图模型

　　当将E-R模型转换成图模型时，需要遵守如下规则：
　　（1）一行仅表示一个节点（node）
　　（2）一个表名对应一个Label名
　　NorthWind dataset表示成图模型的一个局部示意图如下：
　　
　　＃图模型和Ｅ-R模型的区别：
　　（1）前者的节点和边没有空值，而后者的字段存在空值；（2）前者描述“关系”（通过边）更加详尽，而且边可以添加元数据；（3）前者对于描述网络关系更加标准化。

2.3、将数据导出成CSV

　　通过copy和export将PostgreSQL中的部分表导出：

COPY (SELECT * FROM customers) TO '/tmp/customers.csv' WITH CSV header;COPY (SELECT * FROM suppliers) TO '/tmp/suppliers.csv' WITH CSV header;COPY (SELECT * FROM products)  TO '/tmp/products.csv' WITH CSV header;COPY (SELECT * FROM employees) TO '/tmp/employees.csv' WITH CSV header;COPY (SELECT * FROM categories) TO '/tmp/categories.csv' WITH CSV header;COPY (SELECT * FROM ordersLEFT OUTER JOIN order_details ON order_details.OrderID = orders.OrderID) TO '/tmp/orders.csv' WITH CSV header;
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2.4、基于Cypher导入数据

　　通过Cypher的LOAD CSV实现数据导入
　　（1）创建节点
　　import_csv.cypher如下：

// Create customers
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:customers.csv" AS row
CREATE (:Customer {companyName: row.CompanyName, customerID: row.CustomerID, fax: row.Fax, phone: row.Phone});// Create products
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:products.csv" AS row
CREATE (:Product {productName: row.ProductName, productID: row.ProductID, unitPrice: toFloat(row.UnitPrice)});// Create suppliers
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:suppliers.csv" AS row
CREATE (:Supplier {companyName: row.CompanyName, supplierID: row.SupplierID});// Create employees
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:employees.csv" AS row
CREATE (:Employee {employeeID:row.EmployeeID,  firstName: row.FirstName, lastName: row.LastName, title: row.Title});// Create categories
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:categories.csv" AS row
CREATE (:Category {categoryID: row.CategoryID, categoryName: row.CategoryName, description: row.Description});USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:orders.csv" AS row
MERGE (order:Order {orderID: row.OrderID}) ON CREATE SET order.shipName =  row.ShipName;
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　　（2）创建索引
　　对刚创建的节点建立索引，以便在下一步创建边关系的时候能快速检索到各点。

CREATE INDEX ON :Product(productID);CREATE INDEX ON :Product(productName);CREATE INDEX ON :Category(categoryID);CREATE INDEX ON :Employee(employeeID);CREATE INDEX ON :Supplier(supplierID);CREATE INDEX ON :Customer(customerID);CREATE INDEX ON :Customer(customerName);
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　　（3）创建边关系
　　首先创建products和employees的边关系。

USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:orders.csv" AS row
MATCH (order:Order {orderID: row.OrderID})
MATCH (product:Product {productID: row.ProductID})
MERGE (order)-[pu:PRODUCT]->(product)
ON CREATE SET pu.unitPrice = toFloat(row.UnitPrice), pu.quantity = toFloat(row.Quantity);USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:orders.csv" AS row
MATCH (order:Order {orderID: row.OrderID})
MATCH (employee:Employee {employeeID: row.EmployeeID})
MERGE (employee)-[:SOLD]->(order);USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:orders.csv" AS row
MATCH (order:Order {orderID: row.OrderID})
MATCH (customer:Customer {customerID: row.CustomerID})
MERGE (customer)-[:PURCHASED]->(order);
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　　其次，创建products, suppliers, and categories的边关系.

USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:products.csv" AS row
MATCH (product:Product {productID: row.ProductID})
MATCH (supplier:Supplier {supplierID: row.SupplierID})
MERGE (supplier)-[:SUPPLIES]->(product);USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:products.csv" AS row
MATCH (product:Product {productID: row.ProductID})
MATCH (category:Category {categoryID: row.CategoryID})
MERGE (product)-[:PART_OF]->(category);
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　　然后，创建employees之间的“REPORTS_TO”关系。

USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:employees.csv" AS row
MATCH (employee:Employee {employeeID: row.EmployeeID})
MATCH (manager:Employee {employeeID: row.ReportsTo})
MERGE (employee)-[:REPORTS_TO]->(manager);
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　　最后，为优化查询速度，在orders上创建唯一性约束：

CREATE CONSTRAINT ON (o:Order) ASSERT o.orderID IS UNIQUE;
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　　此外，也可以通过运行整个脚本一次性完成所上述工作：

bin/neo4j-shell -path northwind.db -file import_csv.cypher.
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　　（４）最终成果
　　
　　附：（1）Northwind SQL, CSV and Cypher data files (zip)
　　（2）Tool:SQL to Neo4j Import

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