Aggregation Framework Operators

$match operator

• A filter operator, which allows only documents that satisfy specified criteria in the operator to pass ahead in the pipeline.

• If match is the first stage of pipeline, then it can take advantage of indexes.

• We can use multiple $match operator in a single pipeline.

• When using $match operator, we cannot use $where operator.

• We can use only $text query operator if $match stage should be the first stage of pipeline.

• $match operator does not allow projections.

• Example:

  • A sample query on a collection named movies with following criteria,

    • imdb.rating is at least 7

    • genres does not contain "Crime" or "Horror"

    • rated is either "PG" or "G"

    • languages contains "English" and "Japanese"

        db.movies.aggregate([
        { $match: {
            "imdb.rating": { "$gte": 7 },
            "genres": { "$nin": [ "Crime", "Horror" ] } ,
            "rated": { "$in": ["PG", "G" ] },
            "languages": { "$all": [ "English", "Japanese" ] }
            }
        }])

$project operator

• A map like operator, which applies some transformation among collection.

• Once we specified one field to retain, we must specify all fields we want to retain. The _id field is only exception.

• It lets us add new fields.

• This operator can be used as many times as required within an aggregation pipeline.

• It can also be used to re assign values to existing field names, and to derive entirely new fields.

• Example:

  • Adding project to above example

      var pipeline = [{$match: {
      "imdb.rating": { "$gte": 7 },
      "genres": { "$nin": [ "Crime", "Horror" ] } ,
      "rated": { "$in": ["PG", "G" ] },
      "languages": { "$all": [ "English", "Japanese" ] }
      }
      },
      {
          "$project": { "_id": 0, "title": 1, "rated": 1 }
      }]

• Example:

      db.movies.aggregate([
      {
          $match: {
          title: {
              $type: "string"
          }
          }
      },
      {
          $project: {
          title: { $split: ["$title", " "] },
          _id: 0
          }
      },
      {
          $match: {
          title: { $size: 1 }
          }
      }])

$addFields operator

• Adds fields to a document.

• It's a transformation operator, just like $project operator.

• It can modify existing fields or add new transformation fields to incoming documents.

$geoNear operator

• Helps in performing geo queries within an aggregation pipeline. (Like $near query operator).

• It must be first stage in the pipeline.

• It can be used with charted collections.

• When perfoming this operation on a collection, the collection must have one and only one 2dsphere index.

• If using 2dsphere, the distance returned is in meters. Else if using legacy coordinates, the distance returned is in radians.

• Syntax

Cursor-like stages

• $count, $skip, $sort, $limit

• Syntax
• For sort stage, we can specify multiple different fields.

• If sort is near the beginning of pipeline i.e., before project and unwind in the group stage, it can take advantage of indexes. Else, it will perform in-memory sort, which will increase memory consumption.

• Sort operation in an aggregation pipeline is limited by default to 100 MB RAM usage. To allow larger dataset handling, diskUse needs to be allowed in aggregation pipeline.

  db.movies.aggregate([
      {stage1},
      {stage2},
      {
        "$sort":{"field":1}  
      }], {allowDiskUse:true})

• The above option, allows us to do excess of 100 MB of memory calculation using disk. If not done so, operation gets terminated in the server.