Retrieve item list by checking multiple attribute values in MongoDB in golang

Question

This question based on MongoDB,How to retrieve selected items retrieve by selecting multiple condition.It is like IN condition in Mysql

SELECT * FROM venuelist WHERE venueid IN (venueid1, venueid2)

I have attached json data structure that I have used.[Ref: JSON STRUCTUE OF MONGODB ].

As an example, it has a venueList then inside the venue list, It has several attribute venue id and sum of user agents name and total count as value.user agents mean user Os,browser and device information. In this case I used os distribution.In that case i was count linux,ubuntu count on particular venueid.

it is like that,

"sum" : [
    {
        "name" : "linux",
        "value" : 12
    },
    {
        "name" : "ubuntu",
        "value" : 4
    }
],

Finally I want to get count of all linux user count by selecting venueid list in one find query in MongoDB.

As example, I want to select all count of linux users by conditioning if venue id VID1212 or VID4343

Ref: JSON STRUCTUE OF MONGODB

{
    "_id" : ObjectId("57f940c4932a00aba387b0b0"),
    "tenantID" : 1,
    "date" : "2016-10-09 00:23:56",
    "venueList" : [
        {
            "id" : “VID1212”,
            "sum" : [
                {
                      "name" : "linux",
                      "value" : 12
                },
                {
                    "name" : "ubuntu",
                    "value" : 4
                }
            ],
            “ssidList” : [    // this is list of ssid’s in venue
                {
                    "id" : “SSID1212”,
                    "sum" : [
                        {
                            "name" : "linux",
                            "value" : 8
                        },
                        {
                            "name" : "ubuntu",
                            "value" : 6
                        }
                    ],
                    “macList” : [  // this is mac list inside particular ssid  ex: this is mac list inside the SSID1212
                        {
                            "id" : “12:12:12:12:12:12”,
                            "sum" : [
                                {
                                    "name" : "linux",
                                    "value" : 12
                                },
                                {
                                    "name" : "ubuntu",
                                    "value" : 1
                                }
                            ]
                        }
                    ]
                }
            ]
        },
        {
            "id" : “VID4343”,
            "sum" : [
                {
                     "name" : "linux",
                     "value" : 2
                }
            ],
            "ssidList" : [
                {
                    "id" : “SSID4343”,
                    "sum" : [
                        {
                            "name" : "linux",
                            "value" : 2
                        }
                    ],
                    "macList" : [
                        {
                            "id" : “43:43:43:43:43:34”,
                            "sum" : [
                                {
                                    "name" : "linux",
                                    "value" : 2
                                }
                            ]
                        }
                    ]
                }
            ]
        }
    ]
}

I am using golang as language to manipulation data with mongoldb using mgo.v2 package

expected out put is :

output

• linux : 12+2 = 14
• ubuntu : 4+0 = 4

Don't consider inner list in venuelist.

Answer 1

You'd need to use the aggregation framework where you would run an aggregation pipeline that first filters the documents in the collection based on the venueList ids using the $match operator.

The second pipeline would entail flattening the venueList and sum subdocument arrays in order for the data in the documents to be processed further down the pipeline as denormalised entries. The $unwind operator is useful here.

A further filter using $match is necessary after unwinding so that only the documents you want to aggregate are allowed into the next pipeline.

The main pipeline would be the $group operator stage which aggregates the filtered documents to create the desired sums using the accumulator operator $sum. For the desired result, you would need to use a tenary operator like $cond to create the independent count fields since that will feed the number of documents to the $sum expression depending on the name value.

Putting this altogether, consider running the following pipeline:

db.collection.aggregate([
    { "$match": { "venueList.id": { "$in": ["VID1212", "VID4343"] } } },
    { "$unwind": "$venueList" },
    { "$match": { "venueList.id": { "$in": ["VID1212", "VID4343"] } } },
    { "$unwind": "$venueList.sum" },    
    {
        "$group": {
            "_id": null,
            "linux": {
                "$sum": {
                    "$cond": [ 
                        { "$eq": [ "$venueList.sum.name", "linux" ] }, 
                        "$venueList.sum.value", 0 
                    ]
                }
            },
            "ubuntu": {
                "$sum": {
                    "$cond": [ 
                        { "$eq": [ "$venueList.sum.name", "ubuntu" ] }, 
                        "$venueList.sum.value", 0 
                    ]
                }
            }
        }
    }
])

For usage with mGo, you can convert the above pipeline using the guidance in http://godoc.org/labix.org/v2/mgo#Collection.Pipe

---

For a more flexible and better performant alternative which executes much faster than the above, and also takes into consideration unknown values for the sum list, run the alternative pipeline as follows

db.collection.aggregate([
    { "$match": { "venueList.id": { "$in": ["VID1212", "VID4343"] } } },
    { "$unwind": "$venueList" },
    { "$match": { "venueList.id": { "$in": ["VID1212", "VID4343"] } } },
    { "$unwind": "$venueList.sum" },    
    { 
        "$group": {
            "_id": "$venueList.sum.name",
            "count": { "$sum": "$venueList.sum.value" }
        }
    },
    { 
        "$group": {
            "_id": null,
            "counts": {
                "$push": {
                    "name": "$_id",
                    "count": "$count"
                }
            }
        }
    }
])