Question

我正在尝试在neo4j中创建一个庞大的数据库，该数据库将拥有大约200万个节点和大约400万个边缘。我已经能够通过在每个1000个节点的批次中创建节点来加速节点创建过程。但是，当我尝试在这些节点之间创建边时，该过程会减慢然后超时。最初我虽然它可能很慢，因为我在节点名称的基础上合并，但即使我使用ID它也慢 - 我手动创建这些ID。下面我给出了数据和代码，以便更好地理解问题 -

Node.csv - 此文件包含有关节点
的详细信息
NodeName NodeType NodeId Sachin Person 1 UNO Organisation 2 Obama Person 3 Cricket Sports 4 Tennis Sports 5 USA Place 6 India Place 7
Edges.csv - 此文件只包含节点ID及其关系

Node1Id Relationship Node2Id 1 Plays 4 3 PresidentOf 6 1 CitizenOf 7

创建节点的代码如下 -

from py2neo import Graph
graph = Graph()
statement =""
tx = graph.cypher.begin()
for i in range(len(Node)):
    statement = "Create(n{name:{A} ,label:{C}, id:{B}})"
    tx.append(statement,{"A": Node[i][0],"C":str(Node[i][1]), "B":str(Node[i][2])})
    if i % 1000 == 0:
        print str(i) + "Node Created"
        tx.commit()
        tx = self.graph.cypher.begin()
        statement =""

上面的代码就像奇迹一样，在5分钟内创建了200万个节点。创建边的代码如下 -

tx = graph.cypher.begin()
statement = ""
for i in range(len(Edges)):
    statement = "MATCH (a {id:{A}}), (b {id:{B}}) CREATE (a)-[:"+ Edges[i][1]+"]->(b)"
    tx.append(statement, {"A": Edges[i][0], "B": Edges[i][2]})
        if i % 1000 == 0:
            print str(i) + " Relationship Created"
            tx.commit()
            tx = graph.cypher.begin()
            statement = ""

上面，代码适用于创建前1000个关系，但在此之后需要花费大量时间并且连接会超时。

我迫切需要解决这个问题，任何可以加强关系创建过程的帮助都会非常有用。

请注意 - 我没有使用Neo4j或Neo4j shell导入的导入csv，因为它们假设要修复的节点之间的关系。虽然对我来说关系各不相同，但一次导入一个关系是不可行的，因为这意味着手动导入近2000次。

Answer 1

您忘记为节点使用标签，然后在标签+ id上创建约束。

create constraint on (o:Organization) assert o.id is unique;
create constraint on (p:Person) assert p.id is unique;

Create(n:Person {name:{A} ,id:{B}})
Create(n:Organization {name:{A} ,id:{B}})

match (p:Person {id:{p_Iid}), (o:Organization {id:{o_id}})
create (p)-[:WORKS_FOR]->(o);

Answer 2

这是代码的更新版本，因为不推荐使用py2neo（v3 +）事务中的许多内容。该代码还包括Michaels解决方案。

节点：

def insert_nodes_to_neodb():
    queries_per_transaction = 1000  # 1000 seems to work faster
    node_path = "path_to_csv"

    graph = Graph("bolt://localhost:7687", user="neo4j", password="pswd")
    trans_action = graph.begin()

    with open(node_path) as csvfile:
        next(csvfile)   # labels of the columns
        node_csv = csv.reader(csvfile, delimiter=',')
        for idx, row in enumerate(node_csv):
            statement = "CREATE (n:Entity {id:{A} , label:{B}, name:{B}})"  # name is for visual reasons (neo4j)
            trans_action.run(statement, {"A": row[0], "B": row[1]})

            if idx % queries_per_transaction == 0:
                trans_action.commit()
                trans_action = graph.begin()

        # Commit the left over queries
        trans_action.commit()

        # We need to create indexes on a separate transaction
        # neo4j.exceptions.Forbidden: Cannot perform schema updates in a transaction that has performed data updates.
        trans_action = graph.begin()
        trans_action.run("CREATE CONSTRAINT ON (o:Entity) ASSERT o.id IS UNIQUE;")
        trans_action.commit()

边缘：

def insert_edges_to_neodb(neo_graph):
    queries_per_transaction = 1000  # 1000 seems to work faster
    edge_path = "path_to_csv"
    graph = Graph("bolt://localhost:7687", user="neo4j", password="pswd")

    trans_action = graph.begin()

    with open(edge_path) as csvfile:
        next(csvfile)   # labels of the columns
        edge_csv = csv.reader(csvfile, delimiter=',')
        for idx, row in enumerate(edge_csv):
            statement = """MATCH (a:Entity),(b:Entity)
                        WHERE a.id = {A} AND b.id = {B}
                        CREATE (a)-[r:CO_APPEARS { name: a.name + '<->' + b.name, weight: {C} }]->(b)
                        RETURN type(r), r.name"""
            trans_action.run(statement, {"A": row[0], "B": row[1], "C": row[2]})

            if idx % queries_per_transaction == 0:
                trans_action.commit()
                trans_action = graph.begin()

        trans_action.commit()

使用Py2Neo

2 个答案: