我们有一个mongo集合messages，其格式如下：
/* 0 */
{
"text" : "A message to John",
"created" : ISODate("2015-01-29T23:50:10.488Z"),
"to" : {
"id" : ObjectId("54bf1dc6c65b030c00faec0d"),
"name" : "John Smith"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin Fowler"
},
}
/* 1 */
{
"text" : "Another message to John",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1dc6c65b030c00faec0d"),
"name" : "John Smith"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin fowler"
},
}
/* 2 */
{
"text" : "Just another message to Jerry",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1e80eb5bf8800b0f5a8d"),
"name" : "Jerry Jones"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin Fowler"
},
}
/* 2 */
{
"text" : "Message to Martin Fowler",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1e80eb5bf8800b0f5a8d"),
"name" : "Martin Fowler"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Jerry Jones"
},
}
我们需要以对话格式显示上面的数据，然后将每个对话分组在一起。对话意味着它可以是
to或from。我们需要的数据示例如下所示：
{
"result":[
{
"id":"54bf1dc6c65b030c00faec0d",
"name":"Jerry Jones",
"messages":[
{
"text" : "A message to John",
"created" : ISODate("2015-01-29T23:50:10.488Z"),
"to" : {
"id" : ObjectId("54bf1dc6c65b030c00faec0d"),
"name" : "John Smith"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin Fowler"
},
}
{
"text" : "Another message to John",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1dc6c65b030c00faec0d"),
"name" : "John Smith"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin fowler"
},
}
]
},
{
"id":"54bf1e80eb5bf8800b0f5a8d",
"name":"John Smith",
"messages":[
{
"text" : "Just another message to Jerry",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1e80eb5bf8800b0f5a8d"),
"name" : "Jerry Jones"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin Fowler"
},
}
{
"text" : "Message to Martin Fowler",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1e80eb5bf8800b0f5a8d"),
"name" : "Martin Fowler"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Jerry Jones"
},
}
]
}
]
}
注意此查询总是在
current user的上下文中进行的，这就是为什么在每个对话中，我们都有一个_id和name代表对话中的另一个用户的原因。对于上面的示例，current user将为Martin Fowler我们尝试了几种不同的方法来实现此目的，但是仍然遇到问题。我宁愿转向Mongo / Node社区，以了解如何正确完成它。如果有帮助的话，我们将
mongoose与Node一起使用...我们当前拥有的初始查询实现如下：
Message.find().or([{'from.id':req.user.id},{'to.id':req.user.id}]).exec(function(err,messages){
//NEED TO IMPLEMENT THIS HERE CORRECTLY
});
注意
req.user.id是current user的ID 最佳答案
此解决方案是对类似问题here的先前解决方案的略微修改。
在不一致的情况下，有争议的文件具有成员名称。在整个应用程序/数据库中，Martin Folwer应该是Martin Fowler，而不是Martin fowler。 （请注意小f）。您需要对文档进行此更改。
基于$group和to字段的from消息在一起。
构造一个组密钥-“ message_between”，其值为to和from字段中的值的$concat结果。
邮件从Martin Fowler到Jerry Jones和Jerry Jones到Martin Fowler应该放在一个小组中
这样，我们使结果包含最后一个名称
首先，按字母顺序。因此，对于从MartinFowler到Jerry Jones以及Jerry Jones到Martin Fowler的所有消息，我们的密钥是Martin Fowler and Jerry Jones。
码：
Model.aggregate(
//match all those records which involve the user.
{$match:{$or:[{"to.name":req.user.id},
{"from.name":req.user.id}]}},
{$group:{"_id":{
"message_between":{
$cond:[
{
$gt:[
{$substr:["$to.name",0,1]},
{$substr:["$from.name",0,1]}]
},
{$concat:["$to.name"," and ","$from.name"]},
{$concat:["$from.name"," and ","$to.name"]}
]
},"name":{$cond:[{$eq:["$to.name",
req.user.id]},
"$from.name",
"$to.name"]}
},"messages":{$push:"$$ROOT"}
}
},
{$project:{"_id":0,"name":"$_id.name","messages":1}}
,function(err,resp){
// handle response.
})
o / p：
{
"messages" : [
{
"_id" : ObjectId("54d1d819b62f332e93fbb906"),
"text" : "Just another message to Jerry",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1e80eb5bf8800b0f5a8d"),
"name" : "Jerry Jones"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin Fowler"
}
},
{
"_id" : ObjectId("54d1d819b62f332e93fbb907"),
"text" : "Message to Martin Fowler",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1e80eb5bf8800b0f5a8d"),
"name" : "Martin Fowler"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Jerry Jones"
}
}
],
"name" : "Jerry Jones"
}
{
"messages" : [
{
"_id" : ObjectId("54d1d819b62f332e93fbb904"),
"text" : "A message to John",
"created" : ISODate("2015-01-29T23:50:10.488Z"),
"to" : {
"id" : ObjectId("54bf1dc6c65b030c00faec0d"),
"name" : "John Smith"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin Fowler"
}
},
{
"_id" : ObjectId("54d1d819b62f332e93fbb905"),
"text" : "Another message to John",
"created" : ISODate("2015-01-30T00:37:38.106Z"),
"to" : {
"id" : ObjectId("54bf1dc6c65b030c00faec0d"),
"name" : "John Smith"
},
"from" : {
"id" : ObjectId("54bf1e1ceb5bf8800b0f5a8c"),
"name" : "Martin Fowler"
}
}
],
"name" : "John Smith"
}