Neo4j 4.4.4 实现广度优先遍历算法

首先创建一个图，这里创建的是有向图

CREATE (a:Location {name: 'A'}),
       (b:Location {name: 'B'}),
       (c:Location {name: 'C'}),
       (d:Location {name: 'D'}),
       (e:Location {name: 'E'}),
       (f:Location {name: 'F'}),
       (a)-[:ROAD {cost: 50}]->(b),
       (a)-[:ROAD {cost: 50}]->(c),
       (a)-[:ROAD {cost: 100}]->(d),
       (b)-[:ROAD {cost: 40}]->(d),
       (c)-[:ROAD {cost: 40}]->(d),
       (c)-[:ROAD {cost: 80}]->(e),
       (d)-[:ROAD {cost: 30}]->(e),
       (d)-[:ROAD {cost: 80}]->(f),
       (e)-[:ROAD {cost: 40}]->(f);

给这个图命名：

CALL gds.graph.project(
    'myGraph',
    'Location',
    'ROAD',
    {
        relationshipProperties: 'cost'
    }
)

估计一下算法预计占用的内存

MATCH (source:Location {name: 'A'})
CALL gds.bfs.stream.estimate('myGraph', {
    sourceNode: source
})
YIELD nodeCount, relationshipCount, bytesMin, bytesMax, requiredMemory
RETURN nodeCount, relationshipCount, bytesMin, bytesMax, requiredMemory

开始执行广度优先遍历算法。A是指定的起点名。Location注意修改成自己的名字

MATCH (source:Location{name:'A'})
CALL gds.bfs.stream('myGraph', {
  sourceNode: source
})
YIELD path
RETURN path

看一下具体走的路径

指定深度进行遍历。只遍历深度为1 的。maxDepth=1

MATCH (source:Node{name:'A'})
CALL gds.bfs.stream('myGraph', {
  sourceNode: source,
  maxDepth: 1
})
YIELD path
RETURN path

Started streaming 1 records after 7 ms and completed after 7 ms.

官方原文档在此：
https://neo4j.com/docs/graph-data-science/current/algorithms/bfs/