condtitional aggregate function in mongodb

Question

I have a mongodb that has data as

{
  "_id": "a",
  "reply": "<",
  "criterion": "story"
},
{
  "_id": "b",
  "reply": "<",
  "criterion": "story"
},
{
  "_id": "c",
  "reply": ">",
  "criterion": "story"
}

And I want the result as:

 {
   "criterion": "story",
   "result" : {
                ">" : 1,
                "<" : 2
              } 
 }

I want to aggregate on "criterion". So if I do that there will be 1 document. However, I want to count the number of "<" and ">" and write that in the new key as shown in the json above. That is the logic behind this. Could anyone who has a good idea in mongodb help me with this?

Answer 1

You'd need to use the aggregation framework where you would run an aggregation pipeline that has a $group operator pipeline stage which aggregates the documents to create the desired counts 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. The $cond operator can be used effectively to evaluate the counts based on the reply field value. It takes a logical condition as its first argument (if) and then returns the second argument where the evaluation is true (then) or the third argument where false (else). This converts the true/false boolean evaluated returns into 1 and 0 that will feed into $sum respectively:

"$cond": [
    { "$eq": ["$reply", ">"] },
    1, 0
]

So, if within the document being processed the "$reply" field has a ">" value, the $cond operator feeds the value 1 to the $sum else it sums a zero value.

Use the $project as your final pipeline step as it allows you to reshape each document in the stream, include, exclude or rename fields, inject computed fields, create sub-document fields, using mathematical expressions, dates, strings and/or logical (comparison, boolean, control) expressions. It is similar to SELECT in SQL.

The following pipeline should return the desired result:

Model.aggregate([
    {
        "$group": {
            "_id": "$criterion",
            ">": {
                "$sum": {
                    "$cond": [ 
                        { "$eq": [ "$reply", ">" ] }, 
                        1, 0 
                    ]
                }
            },
            "<": {
                "$sum": {
                    "$cond": [ 
                        { "$eq": [ "$reply", "<" ] }, 
                        1, 0 
                    ]
                }
            }
        }
    },
    {
        "$project": {
            "_id": 0,
            "criterion": "$_id",
            "result.>": "$>",
            "result.<": "$<"
        }
    }
]).exec(function(err, result) {
    console.log(JSON.stringify(result, null, 4));
});

Sample Console Output

{
    "criterion" : "story",
    "result" : {
        ">" : 1,
        "<" : 2
    }
}

Note: This approach takes into consideration the values for the $reply field are fixed and known hence it's not flexible where the values are dynamic and unknown.

---

For a more flexible alternative which executes much faster than the above, has better performance and also takes into consideration unknown values for the count fields, I would suggest running the pipeline as follows:

Model.aggregate([
    { 
        "$group": {
            "_id": {
                "criterion": "$criterion",
                "reply": "$reply"
            },
            "count": { "$sum": 1 }
        }
    },
    { 
        "$group": {
            "_id": "$_id.criterion",
            "result": {
                "$push": {
                    "reply": "$_id.reply",
                    "count": "$count"
                }
            }
        }
    }
]).exec(function(err, result) {
    console.log(JSON.stringify(result, null, 4));
});

Sample Console Output

{
    "_id" : "story",
    "result" : [ 
        {
            "reply" : "<",
            "count" : 2
        }, 
        {
            "reply" : ">",
            "count" : 1
        }
    ]
}