Question

Assuming I have a collection called “posts” (in reality it is a more complex collection, posts is too simple) with the following structure:

> db.posts.find()

{ "_id" : ObjectId("50ad8d451d41c8fc58000003"), "title" : "Lorem ipsum", "author" : 
"John Doe", "content" : "This is the content", "tags" : [ "SOME", "RANDOM", "TAGS" ] }

I expect this collection to span hundreds of thousands, perhaps millions, that I need to query for posts by tags and group the results by tag and display the results paginated. This is where the aggregation framework comes in. I plan to use the aggregate() method to query the collection:

db.posts.aggregate([
  { "$unwind" : "$tags" },
  { "$group" : {
      _id: { tag: "$tags" },
      count: { $sum: 1 }
  } }
]);

The catch is that to create the paginator I would need to know the length of the output array. I know that to do that you can do:

db.posts.aggregate([
  { "$unwind" : "$tags" },
  { "$group" : {
      _id: { tag: "$tags" },
      count: { $sum: 1 }
  } }
  { "$group" : {
      _id: null,
      total: { $sum: 1 }
  } }
]);

But that would discard the output from previous pipeline (the first group). Is there a way that the two operations be combined while preserving each pipeline’s output? I know that the output of the whole aggregate operation can be cast to an array in some language and have the contents counted but there may be a possibility that the pipeline output may exceed the 16Mb limit. Also, performing the same query just to obtain the count seems like a waste.

So is obtaining the document result and count at the same time possible? Any help is appreciated.

Answer 1

1. Use $project to save tag and count into tmp
2. Use $push or addToSet to store tmp into your data list.

Code:

db.test.aggregate(
    {$unwind: '$tags'}, 
    {$group:{_id: '$tags', count:{$sum:1}}},
    {$project:{tmp:{tag:'$_id', count:'$count'}}}, 
    {$group:{_id:null, total:{$sum:1}, data:{$addToSet:'$tmp'}}}
)

Output:

{
    "result" : [
            {
                    "_id" : null,
                    "total" : 5,
                    "data" : [
                            {
                                    "tag" : "SOME",
                                    "count" : 1
                            },
                            {
                                    "tag" : "RANDOM",
                                    "count" : 2
                            },
                            {
                                    "tag" : "TAGS1",
                                    "count" : 1
                            },
                            {
                                    "tag" : "TAGS",
                                    "count" : 1
                            },
                            {
                                    "tag" : "SOME1",
                                    "count" : 1
                            }
                      ]
              }
      ],
      "ok" : 1
}