获取ProcessUrecallFailed:未能调用过程:由:org.neo4j.cypher.internal.v3

Question

我正在尝试将CSV文件的动态上传节点上传到Neo4J GraphDB。所以我正在开发一个脚本。这是我的代码

def CreateNodes(filename,label):
    print(filename,label)
    print(type(filename),type(label))
    path=nodesourcefolder+filename
    print(path)
    #filestring=nodesourcefolder+filename
    if(isfile(path)==True):
        print("valid")
        #nodequery="""CALL apoc.periodic.iterate('CALL apoc.load.csv(%s) yield map as row return row','CREATE (p:%s) SET p = row', {batchSize:10000, iterateList:true, parallel:true})"""%(path,label)
        nodequery="""CALL apoc.periodic.iterate('CALL apoc.load.csv("""+path+""") yield map as row return row','CREATE (p:"""+label+""") SET p = row', {batchSize:10000, iterateList:true, parallel:true})"""
        print(nodequery)
    return nodequery   
query=CreateNodes("test.csv","myNode")
graphdriver.run(query)

查询变量给了我值test.csv myNode

out put

<class 'str'> <class 'str'>
/Users/kalyan.admin/NEO4J_HOME/import/test.csv
valid
CALL apoc.periodic.iterate('CALL apoc.load.csv(/Users/kalyan.admin/NEO4J_HOME/import/test.csv) yield map as row return row','CREATE (p:myNode) SET p = row', {batchSize:10000, iterateList:true, parallel:true})

当我要运行Graph Driver.lun(Query(

时

我正在遇到波纹管错误

**ProcedureCallFailed: Failed to invoke procedure `apoc.periodic.iterate`: Caused by: org.neo4j.cypher.internal.v3_5.util.SyntaxException: Invalid input 'U': expected '*' or '/' (line 1, column 44 (offset: 43))**

当我要将文件名，标签名称传递到createNode函数时，我已经获得了字符串文件路径名和标签值。但是我的图形驱动程序不在努力创建节点

请帮助我解决这个问题。我已经尝试了两个节点查询操作，其中一个已注释出来，但是所有这些查询都在运行GraphDriver

Answer 1

您在Cypher查询上有语法问题，文件的路径应为字符串。

这是无效的：

CALL apoc.periodic.iterate(
  'CALL apoc.load.csv(/Users/kalyan.admin/NEO4J_HOME/import/test.csv) yield map as row return row',
  'CREATE (p:myNode) SET p = row', 
  {batchSize:10000, iterateList:true, parallel:true}
)

这是(请注意路径周围的双引号(：

CALL apoc.periodic.iterate(
  'CALL apoc.load.csv("/Users/kalyan.admin/NEO4J_HOME/import/test.csv") yield map as row return row',
  'CREATE (p:myNode) SET p = row', 
  {batchSize:10000, iterateList:true, parallel:true}
)