图快速入门

图表快速入门

先决条件

对于这个快速入门教程，你需要：

使用redis-cli绘制图形

首先，连接到您的数据库使用redis-cli。

创建图表

当你创建一个图时，你可以用这种格式定义节点和它们之间的关系：

(:)-[:]->(:)

要在单个创建查询中定义多个节点和关系，请用逗号分隔条目。

例如，使用CREATE查询来创建一个新的摩托车手和参加MotoGP联赛的团队的图：

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

您可以向先前创建的图形添加新节点：

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

在图的节点之间创建新的关系：

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命令来查询图的数据。

以下示例返回哪些摩托车骑手为雅马哈车队参赛：

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"

你也可以使用functions来创建更复杂的查询。

例如，您可以使用count函数来检查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

你可以使用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

你也可以使用DELETE查询来删除节点的关系而不移除任何节点：

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"

删除一个图

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绘制图形

如果你想在应用程序中使用图表，你可以使用这些客户端库。

以下示例使用了Redis Python客户端库redis-py，该库自v4.1.0版本起支持图命令。

这段Python代码创建了一个图表，用于表示社交媒体网站上用户之间的友谊关系。它还展示了如何运行查询和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可视化图形

您可以使用Redis Insight工作台来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Workbench按钮：

    The Workbench icon

  3. 在文本编辑器中输入图形查询。

    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，输出日志会显示图形节点和关系的可视化表示：

Visualize a graph with Redis Insight workbench.

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