需要帮助减少合并节点和建立关系的处理时间

Question

我是Cypher的新手。我正在使用GrapheneDB和py2neo（版本2.0.2）

构建一个简单的图形

在我的简单图表中，我有Repository，Organization＆amp; People个节点。 IN_ORGANIZATION和IS_ACTOR是两种类型的关系。以下是用于创建节点和关系的代码段（entire code on GitHub，请参阅第88 - 108行）

    #Create repository node if one does not exist
    r = graph.merge_one("Repository", "id", record["full_name"])
    #Update timestamp with time now in epoch milliseconds
    r.properties["created_at"] = MyMoment.TNEM()
    #Apply property change
    r.push()   
    ...
    #Create organization node if one does not exist
    o = graph.merge_one("Organization", "id", record["organization"])
    #Update timestamp with time now in epoch milliseconds      
    o.properties["created_at"] = MyMoment.TNEM()
    #Apply property change
    o.push()
    rel = Relationship(r,"IN_ORGANIZATION",o)
    #create unique relation between repository and organization
    #ignore if relation already exists
    graph.create_unique(rel)
    ...
    #Create actor relation if one does not exist
    p = graph.merge_one("People", "id", al)
    #Update timestamp with time now in epoch milliseconds          
    p.properties["created_at"] = MyMoment.TNEM()
    p.push()
    rel = Relationship(r,"IS_ACTOR",p)
    #create unique relation between repository and people
    #ignore if relation already exists
    graph.create_unique(rel)

以上代码适用于小型数据集。当数据集增长时，每小时创建/合并约20K节点和~15K关系，处理时间长于一小时（有时几小时）。我需要减少处理时间。我可以探索哪些其他备选方案？我在考虑批处理模式？如何将其与merge_one和create_unique一起使用？有什么想法吗？