Question

我正在尝试将CSV文件加载到GrapheneDB上托管的Neo4j数据库中。它在5000行的第一个文件上工作正常。完成此文件大约需要16秒。

我现在正在导入具有相同架构和相同行数的第二个文件。数据不同。 Cypher查询已运行超过30分钟，但仍未完成。我不知道它在做什么，为什么它这么慢。这是我的密码：

USING PERIODIC COMMIT 500
LOAD CSV WITH HEADERS FROM 'http://example.com/some.csv' AS line
Match (c:Customer {customerID: line.CustomerID}) 
MERGE (c)<-[r:DEPT_OF]-(dept:Dept { name: line.Category})
ON CREATE 
SET dept.name = line.Category, dept.deptID=line.DeptID, dept.createdDTS=1453478149463
MERGE (dept)<-[r1:IN_DEPT]-(pt:ProductType {name: dept.name}) 
ON CREATE 
SET pt.name = dept.name, pt.packQty = line.PackQty, pt.createdDTS = 1453478149463, 
pt.productTypeID = line.ProductTypeID
MERGE (pt)<-[r2:OF_TYPE]-(st:Style {name: line.Style})
ON CREATE 
SET st.name = line.Style, st.styleID = line.StyleID, st.styleNum = line.StyleNo, st.price = line.Price
MERGE (st)<-[r3:OF_STYLE]-(p:Product {productNum: line.UPC})
ON CREATE 
SET p.floorMin = line.MinFloor, p.floorMax = line.FloorMax, p.color = line.Color, p.createdDTS = 1453478149463,
p.size = line.Size, p.productID = line.ProductID;

对于来自我的csv的行：

UPC,Category,Style,StyleNo,Color,Size,MinFloor,MaxFloor,Price,ProductID,CustomerID,ProductType,PackQty,DeptID,StyleID,ProductTypeID,ProductID
33383605005,FRESH VEGETABLES,GREEN ONIONS 24/10 OZ,NA,NA,NA,0,0,1.79,,5f795a69-47cb-49c8-a334-0cf5d67be423,FRESH VEGETABLES,1,538a02c6-b6b7-4d0d-8dca-5ff3a513d59e,3e08dabb-415a-4826-86e8-44efb9813892,cc6a0f3c-1c05-44a0-b603-37cbbb60954e,3324b2b1-954a-4547-a82d-553be66d7b54
52867010005,FRESH VEGETABLES,GREEN ONIONS 24/10 OZ,NA,NA,NA,0,0,1.79,,5f795a69-47cb-49c8-a334-0cf5d67be423,FRESH VEGETABLES,1,edfa998f-3749-4d1f-bd96-3f4a5db0de67,fb11a8e5-de49-44da-924a-9ebc5f7f01d2,d47fd5d8-dbf0-4110-b701-543e6ed0ae40,28a9d206-96c6-4fe4-b528-84e446ba3c16

更新1：

我根据Nicole的回复添加了以下索引。

CREATE INDEX ON：客户（customerID）
创建指数：部门（名称）
CREATE INDEX ON：ProductType（name）
CREATE INDEX ON：样式（名称）
创建INDEX ON：产品（productNum）

这有很多帮助，但是对于5K行仍然需要大约20秒。这是正常的吗？

感谢任何帮助。

更新2：

基于@michael的回复，我进一步研究了一下，发现以下文章非常有用：

http://graphaware.com/neo4j/2014/07/31/cypher-merge-explained.html

更新3：

我已将我的密码更新为以下内容以避免重复。我希望这看起来不错？

USING PERIODIC COMMIT 500
LOAD CSV WITH HEADERS FROM '...' AS line
Match (c:Customer {customerID: line.CustomerID}) 
MERGE (c)<-[r:DEPT_OF]-(dept:Dept { name: line.Category })
ON CREATE 
SET dept.name = dept.name, dept.deptID=line.categoryID, dept.createdDTS=1453742532269, dept.modifiedDTS = 1453742532269
MERGE (c)<-[r22:DEPT_OF]-(dept)
MERGE (dept)<-[r1:IN_DEPT]-(pt:ProductType {name: dept.name}) 
ON CREATE 
SET pt.name = dept.name, pt.packQty = line.PackQty, pt.createdDTS = 1453742532269, pt.productTypeID = line.ProductTypeID, pt.modifiedDTS = 1453742532269
MERGE (c)<-[r2:DEPT_OF]-(dept)
MERGE (dept)<-[r3:IN_DEPT]-(pt) 
MERGE (pt)<-[r4:OF_TYPE]-(st:Style {name: line.Style})
ON CREATE 
SET st.name = line.Style, st.styleID = line.StyleID, st.styleNum = line.StyleNo, st.price = line.Price, st.modifiedDTS = 1453742532269, st.createdDTS = 1453742532269
MERGE (c)<-[r5:DEPT_OF]-(dept)
MERGE (dept)<-[r6:IN_DEPT]-(pt) 
MERGE (pt)<-[r7:OF_TYPE]-(st)
MERGE (st)<-[r8:OF_STYLE]-(p:Product {productNum: line.UPC})
ON CREATE 
SET p.floorMin = line.MinFloor, p.floorMax = line.FloorMax, p.color = line.Color, p.createdDTS = 1453742532269,p.modifiedDTS = 1453742532269, p.size = line.Size, p.productID = line.ProductID;

neo4j加载csv非常慢

0 个答案: