由于MongoDB最近引入了graphLookup,我试图找出是否可以保存一个简单的社交关系图。我目前正在使用neo4j。
我理解graphLookup是一种递归搜索,它只是通过“ConnectFromField”进行更深入的搜索。每个文件。
虽然我能够做基本的东西,但我想为每个关系提供更多属性。例如,这里的第一个例子是:(员工和报告层次结构)
https://docs.mongodb.com/manual/reference/operator/aggregation/graphLookup/
{ "_id" : 2, "name" : "Eliot", "reportsTo" : "Dev" }
如果我需要在' reportsTo'中添加开始日期价值,像这样:
{ "_id" : 2, "name" : "Eliot", "reportsTo" : {"name": "Dev", "from": "date" } }
我担心这不受支持。
我想知道是否有人以这种方式使用过MongoDB。
答案 0 :(得分:6)
说我们已插入以下文件:
> db.employees.insertMany([
... { "_id" : 1, "name" : "Dev" },
... { "_id" : 2, "name" : "Eliot", "reportsTo" : { name: "Dev", "from": ISODate("2016-01-01T00:00:00.000Z") } },
... { "_id" : 3, "name" : "Ron", "reportsTo" : { name: "Eliot", "from": ISODate("2016-01-01T00:00:00.000Z") } },
... { "_id" : 4, "name" : "Andrew", "reportsTo" : { name: "Eliot", "from": ISODate("2016-01-01T00:00:00.000Z") } },
... { "_id" : 5, "name" : "Asya", "reportsTo" : { name: "Ron", "from": ISODate("2016-01-01T00:00:00.000Z") } },
... { "_id" : 6, "name" : "Dan", "reportsTo" : { name: "Andrew", "from": ISODate("2016-01-01T00:00:00.000Z") } },
... ]);
{ "acknowledged" : true, "insertedIds" : [ 1, 2, 3, 4, 5, 6 ] }
然后,我们可以使用.
使用以下聚合查询从嵌入文档中获取字段:
db.employees.aggregate([
{
$graphLookup: {
from: "employees",
startWith: "Eliot",
connectFromField: "reportsTo.name",
connectToField: "name",
as: "reportingHierarchy"
}
}
])
然后会返回以下结果:
{
"_id" : 1,
"name" : "Dev",
"reportingHierarchy" : [
{
"_id" : 1,
"name" : "Dev"
},
{
"_id" : 2,
"name" : "Eliot",
"reportsTo" : {
"name" : "Dev",
"from" : ISODate("2016-01-01T00:00:00Z")
}
}
]
}
{
"_id" : 2,
"name" : "Eliot",
"reportsTo" : {
"name" : "Dev",
"from" : ISODate("2016-01-01T00:00:00Z")
},
"reportingHierarchy" : [
{
"_id" : 1,
"name" : "Dev"
},
{
"_id" : 2,
"name" : "Eliot",
"reportsTo" : {
"name" : "Dev",
"from" : ISODate("2016-01-01T00:00:00Z")
}
}
]
}
{
"_id" : 3,
"name" : "Ron",
"reportsTo" : {
"name" : "Eliot",
"from" : ISODate("2016-01-01T00:00:00Z")
},
"reportingHierarchy" : [
{
"_id" : 1,
"name" : "Dev"
},
{
"_id" : 2,
"name" : "Eliot",
"reportsTo" : {
"name" : "Dev",
"from" : ISODate("2016-01-01T00:00:00Z")
}
}
]
}
{
"_id" : 4,
"name" : "Andrew",
"reportsTo" : {
"name" : "Eliot",
"from" : ISODate("2016-01-01T00:00:00Z")
},
"reportingHierarchy" : [
{
"_id" : 1,
"name" : "Dev"
},
{
"_id" : 2,
"name" : "Eliot",
"reportsTo" : {
"name" : "Dev",
"from" : ISODate("2016-01-01T00:00:00Z")
}
}
]
}
{
"_id" : 5,
"name" : "Asya",
"reportsTo" : {
"name" : "Ron",
"from" : ISODate("2016-01-01T00:00:00Z")
},
"reportingHierarchy" : [
{
"_id" : 1,
"name" : "Dev"
},
{
"_id" : 2,
"name" : "Eliot",
"reportsTo" : {
"name" : "Dev",
"from" : ISODate("2016-01-01T00:00:00Z")
}
}
]
}
{
"_id" : 6,
"name" : "Dan",
"reportsTo" : {
"name" : "Andrew",
"from" : ISODate("2016-01-01T00:00:00Z")
},
"reportingHierarchy" : [
{
"_id" : 1,
"name" : "Dev"
},
{
"_id" : 2,
"name" : "Eliot",
"reportsTo" : {
"name" : "Dev",
"from" : ISODate("2016-01-01T00:00:00Z")
}
}
]
}
然后我们还可以使用聚合管道的其余部分来执行任何其他操作:
db.employees.aggregate([
{ $match: { "reportsTo.from": { $gt: ISODate("2016-01-01T00:00:00Z") } } },
{ $graphLookup: { ... } },
{ $project: { ... }
]);
有关管道阶段,请参阅https://docs.mongodb.com/v3.2/reference/operator/aggregation-pipeline/。