在 MongDB 3.2 中，这可以使用$unwind运算符来完成，您可以在其中传递带有字段path和includeArrayIndex将保存数组索引的字段的对象：
pipeline = [
{ "$match": {"name": "somename"} },
{ "$unwind": { "path": "$values", "includeArrayIndex": "position" } },
{
"$project": {
"name": 1,
"newarray.position": "$position",
"newarray.user_name": "$values.user_name",
"newarray.value_date": "$values.value_date",
"newarray.value": "$values.value",
}
},
{
"$group": {
"_id": "$name",
"values": { "$push": "$newarray" }
}
}
]
db.test.aggregate(pipeline);
输出
> db.test.aggregate(pipeline).pretty();
{
"_id" : "somename",
"values" : [
{
"position" : NumberLong(0),
"user_name" : "guest8911",
"value_date" : "2016-03-09T14:40:34.512Z",
"value" : 8911
},
{
"position" : NumberLong(1),
"user_name" : "guest7485",
"value_date" : "2016-03-07T14:11:05.217Z",
"value" : 539
},
{
"position" : NumberLong(2),
"user_name" : "guest7485",
"value_date" : "2016-03-07T14:11:08.853Z",
"value" : 221
},
{
"position" : NumberLong(3),
"user_name" : "guest7485",
"value_date" : "2016-03-07T14:11:12.377Z",
"value" : 77
}
]
}
>
如果 mgo 驱动程序不支持此功能，那么为此使用 Map-Reduce 是一种不太有效的方法。以下 mongo shell 示例演示了如何运行该操作：
填充测试集合：
db.test.insert({
"name": "somename",
"values": [
{
"user_name": "guest8911",
"value": 8911,
"value_date": "2016-03-09T14:40:34.512Z"
},
{
"user_name": "guest7485",
"value": 539,
"value_date": "2016-03-07T14:11:05.217Z"
},
{
"user_name": "guest7485",
"value": 221,
"value_date": "2016-03-07T14:11:08.853Z"
},
{
"user_name": "guest7485",
"value": 77,
"value_date": "2016-03-07T14:11:12.377Z"
}
]
})
运行以下 map-reduce 操作：
> mr = db.runCommand({
"mapreduce": "test",
"map": function() {
var arr = []
for(var i=0; i < this.values.length; i++){
var val = this.values[i];
val["position"] = i+1;
arr.push(val);
}
emit(this._id, arr);
},
"reduce" : function() {},
"out": "test_keys"
})
查询结果集合：
> db[mr.result].find().pretty()
{
"_id" : ObjectId("56e18ab84b9018ec86d2a6bd"),
"value" : [
{
"user_name" : "guest8911",
"value" : 8911,
"value_date" : "2016-03-09T14:40:34.512Z",
"position" : 1
},
{
"user_name" : "guest7485",
"value" : 539,
"value_date" : "2016-03-07T14:11:05.217Z",
"position" : 2
},
{
"user_name" : "guest7485",
"value" : 221,
"value_date" : "2016-03-07T14:11:08.853Z",
"position" : 3
},
{
"user_name" : "guest7485",
"value" : 77,
"value_date" : "2016-03-07T14:11:12.377Z",
"position" : 4
}
]
}
>
现在给出上面的清单，您可以使用 MapReduce 在 mgo 中组装您的查询
job := mgo.MapReduce{
Map: "function(){var arr=[];for(var i=0;i<this.values.length; i++){var val=this.values[i];val['position']=i+1;arr.push(val);};emit(this._id,arr);}",
Reduce: "function() { }",
}
var result []struct { Id int "_id"; Value []EValue }
_, err := collection.Find(nil).MapReduce(job, &result)
if err != nil {
panic(err)
}
for _, item := range result {
fmt.Println(item.Value)
}
有关更多详细信息，请查看文档：https : //godoc.org/labix.org/v1/mgo#MapReduce：