图数据库 快速入门

图数据库 快速入门

先决条件

本快速入门教程需要

使用 redis-cli 的图

首先，使用 redis-cli 连接到您的数据库。

创建图

创建图时，可以使用以下格式定义节点及其关系

(:<node 1>)-[:<relationship>]->(:<node 2>)

要在一个创建查询中定义多个节点和关系，请使用逗号分隔各个条目。

例如，使用 CREATE 查询创建一个新的摩托车骑手和参加 MotoGP 联赛的团队图

127.0.0.1:12543> GRAPH.QUERY MotoGP "CREATE (:Rider {name:'Valentino Rossi'})-[:rides]->(:Team {name:'Yamaha'}), (:Rider {name:'Dani Pedrosa'})-[:rides]->(:Team {name:'Honda'}), (:Rider {name:'Andrea Dovizioso'})-[:rides]->(:Team {name:'Ducati'})"
1) 1) "Labels added: 2"
   2) "Nodes created: 6"
   3) "Properties set: 6"
   4) "Relationships created: 3"
   5) "Cached execution: 0"
   6) "Query internal execution time: 0.385472 milliseconds"

添加节点

您可以将新节点添加到之前创建的图中

127.0.0.1:12543> GRAPH.QUERY MotoGP "CREATE (:Rider {name:'Jorge Lorenzo'})"
1) 1) "Nodes created: 1"
   2) "Properties set: 1"
   3) "Cached execution: 0"
   4) "Query internal execution time: 0.185841 milliseconds"

添加关系

要创建图中节点之间的新的关系

127.0.0.1:12543> GRAPH.QUERY MotoGP "MATCH (r:Rider), (t:Team) WHERE r.name = 'Jorge Lorenzo' and t.name = 'Honda' CREATE (r)-[:rides]->(t)"
1) 1) "Relationships created: 1"
   2) "Cached execution: 0"
   3) "Query internal execution time: 0.356578 milliseconds"

查询图

创建图后，您可以使用 GRAPH.QUERY 命令查询图中的数据。

以下示例返回哪些摩托车骑手代表雅马哈车队

127.0.0.1:12543> GRAPH.QUERY MotoGP "MATCH (r:Rider)-[:rides]->(t:Team) WHERE t.name = 'Yamaha' RETURN r,t"
1) 1) "r"
   2) "t"
2) 1) 1) 1) 1) "id"
            2) "0"
         2) 1) "labels"
            2) 1) "Rider"
         3) 1) "properties"
            2) 1) 1) "name"
                  2) "Valentino Rossi"
      2) 1) 1) "id"
            2) "1"
         2) 1) "labels"
            2) 1) "Team"
         3) 1) "properties"
            2) 1) 1) "name"
                  2) "Yamaha"
3) 1) "Cached execution: 0"
   2) "Query internal execution time: 0.500535 milliseconds"

您还可以使用 函数 创建更复杂的查询。

例如，您可以使用 count 函数查看有多少骑手代表本田车队

127.0.0.1:12543> GRAPH.QUERY MotoGP "MATCH (r:Rider)-[:rides]->(t:Team {name:'Honda'}) RETURN count(r)"
1) 1) "count(r)"
2) 1) 1) "2"
3) 1) "Cached execution: 0"
   2) "Query internal execution time: 0.445760 milliseconds"

删除节点

您可以使用 DELETE 查询从图中删除特定节点及其关系

127.0.0.1:12543> GRAPH.QUERY MotoGP "MATCH (r:Rider {name: 'Dani Pedrosa'}) DELETE r"
1) 1) "Nodes deleted: 1"
   2) "Relationships deleted: 1"
   3) "Cached execution: 0"
   4) "Query internal execution time: 0.276815 milliseconds"

删除关系

您也可以使用 DELETE 查询删除节点的关系，而不删除任何节点

127.0.0.1:12543> GRAPH.QUERY MotoGP "MATCH (:Rider {name: 'Valentino Rossi'})-[r:rides]->() DELETE r"
1) 1) "Relationships deleted: 1"
   2) "Cached execution: 0"
   3) "Query internal execution time: 0.348346 milliseconds"

删除图

要删除整个图（包括所有节点和关系），请运行 GRAPH.DELETE 命令

127.0.0.1:12543> GRAPH.DELETE MotoGP
"Graph removed, internal execution time: 0.013138 milliseconds"

使用 Python 的图

如果您想在应用程序中使用图，可以使用以下 客户端库 之一。

以下示例使用 Redis Python 客户端库 redis-py，该库从 v4.1.0 版本开始支持图命令。

此 Python 代码创建了一个图，表示社交媒体网站上用户之间的友谊。它还展示了如何运行查询以及如何更改用户之间的关系。

import redis
from redis.commands.graph.edge import Edge
from redis.commands.graph.node import Node

# Connect to a database
r = redis.Redis(host="<endpoint>", port="<port>", 
                password="<password>")

# Create nodes that represent users
users = { "Alex": Node(label="Person", properties={"name": "Alex", "age": 35}),
          "Jun": Node(label="Person", properties={"name": "Jun", "age": 33}),
          "Taylor": Node(label="Person", properties={"name": "Taylor", "age": 28}),
          "Noor": Node(label="Person", properties={"name": "Noor", "age": 41}) }

# Define a graph called SocialMedia
social_graph = r.graph("SocialMedia")

# Add users to the graph as nodes
for key in users.keys():
    social_graph.add_node(users[key])

# Add relationships between user nodes
social_graph.add_edge( Edge(users["Alex"], "friends", users["Jun"]) )
# Make the relationship bidirectional
social_graph.add_edge( Edge(users["Jun"], "friends", users["Alex"]) )

social_graph.add_edge( Edge(users["Jun"], "friends", users["Taylor"]) )
social_graph.add_edge( Edge(users["Taylor"], "friends", users["Jun"]) )

social_graph.add_edge( Edge(users["Jun"], "friends", users["Noor"]) )
social_graph.add_edge( Edge(users["Noor"], "friends", users["Jun"]) )

social_graph.add_edge( Edge(users["Alex"], "friends", users["Noor"]) )
social_graph.add_edge( Edge(users["Noor"], "friends", users["Alex"]) )

# Create the graph in the database
social_graph.commit()

# Query the graph to find out how many friends Alex has
result1 = social_graph.query("MATCH (p1:Person {name: 'Alex'})-[:friends]->(p2:Person) RETURN count(p2)")
print("Alex's original friend count:", result1.result_set)

# Delete a relationship without deleting any user nodes
social_graph.query("MATCH (:Person {name: 'Alex'})<-[f:friends]->(:Person {name: 'Jun'}) DELETE f")

# Query the graph again to see Alex's updated friend count
result2 = social_graph.query("MATCH (p1:Person {name: 'Alex'})-[:friends]->(p2:Person) RETURN count(p2)")
print("Alex's updated friend count:", result2.result_set)

# Delete the entire graph
social_graph.delete()

示例输出

$ ./quick_start.py
Alex's original friend count: [[2]]
Alex's updated friend count: [[1]]

使用 Redis Insight 可视化图

您可以使用 Redis Insight 工作台可视化图中节点之间的关系。

  1. 使用 Redis Insight 连接到您的数据库。您可以 手动连接 或使用 自动发现 功能。

  2. 选择 **工作台** 按钮

    The Workbench icon

  3. 在文本编辑器中输入图查询。

    例如，此查询返回图中的所有节点和关系

    GRAPH.QUERY MotoGP "MATCH (n) RETURN n"

  4. 选择 **运行**

    The Run command icon

运行查询后，输出日志将显示图的节点和关系的可视化表示

Visualize a graph with Redis Insight workbench.

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