$bucket (aggregation)

Bucket by Year and Filter by Bucket Results

In mongosh, create a sample collection named artists with the following documents:

db.artists.insertMany([
  { "_id" : 1, "last_name" : "Bernard", "first_name" : "Emil", "year_born" : 1868, "year_died" : 1941, "nationality" : "France" },
  { "_id" : 2, "last_name" : "Rippl-Ronai", "first_name" : "Joszef", "year_born" : 1861, "year_died" : 1927, "nationality" : "Hungary" },
  { "_id" : 3, "last_name" : "Ostroumova", "first_name" : "Anna", "year_born" : 1871, "year_died" : 1955, "nationality" : "Russia" },
  { "_id" : 4, "last_name" : "Van Gogh", "first_name" : "Vincent", "year_born" : 1853, "year_died" : 1890, "nationality" : "Holland" },
  { "_id" : 5, "last_name" : "Maurer", "first_name" : "Alfred", "year_born" : 1868, "year_died" : 1932, "nationality" : "USA" },
  { "_id" : 6, "last_name" : "Munch", "first_name" : "Edvard", "year_born" : 1863, "year_died" : 1944, "nationality" : "Norway" },
  { "_id" : 7, "last_name" : "Redon", "first_name" : "Odilon", "year_born" : 1840, "year_died" : 1916, "nationality" : "France" },
  { "_id" : 8, "last_name" : "Diriks", "first_name" : "Edvard", "year_born" : 1855, "year_died" : 1930, "nationality" : "Norway" }
])

The following operation groups the documents into buckets according to the year_born field and filters based on the count of documents in the buckets:

db.artists.aggregate( [
  // First Stage
  {
    $bucket: {
      groupBy: "$year_born",                        // Field to group by
      boundaries: [ 1840, 1850, 1860, 1870, 1880 ], // Boundaries for the buckets
      default: "Other",                             // Bucket ID for documents which do not fall into a bucket
      output: {                                     // Output for each bucket
        "count": { $sum: 1 },
        "artists" :
          {
            $push: {
              "name": { $concat: [ "$first_name", " ", "$last_name"] },
              "year_born": "$year_born"
            }
          }
      }
    }
  },
  // Second Stage
  {
    $match: { count: {$gt: 3} }
  }
] )

First Stage

The $bucket stage groups the documents into buckets by the year_born field. The buckets have the following boundaries:

• [1840, 1850) with inclusive lowerbound 1840 and exclusive upper bound 1850.

• [1850, 1860) with inclusive lowerbound 1850 and exclusive upper bound 1860.

• [1860, 1870) with inclusive lowerbound 1860 and exclusive upper bound 1870.

• [1870, 1880) with inclusive lowerbound 1870 and exclusive upper bound 1880.

• If a document did not contain the year_born field or its year_born field was outside the ranges above, it would be placed in the default bucket with the _id value "Other".

The stage includes the output document to determine the fields to return:

Field	Description
_id	Inclusive lower bound of the bucket.
count	Count of documents in the bucket.
artists	Array of documents containing information on each artist in the bucket. Each document contains the artist's name, which is a concatenation (i.e. $concat) of the artist's first_name and last_name. year_born

This stage passes the following documents to the next stage:

{ "_id" : 1840, "count" : 1, "artists" : [ { "name" : "Odilon Redon", "year_born" : 1840 } ] }
{ "_id" : 1850, "count" : 2, "artists" : [ { "name" : "Vincent Van Gogh", "year_born" : 1853 },
                                           { "name" : "Edvard Diriks", "year_born" : 1855 } ] }
{ "_id" : 1860, "count" : 4, "artists" : [ { "name" : "Emil Bernard", "year_born" : 1868 },
                                           { "name" : "Joszef Rippl-Ronai", "year_born" : 1861 },
                                           { "name" : "Alfred Maurer", "year_born" : 1868 },
                                           { "name" : "Edvard Munch", "year_born" : 1863 } ] }
{ "_id" : 1870, "count" : 1, "artists" : [ { "name" : "Anna Ostroumova", "year_born" : 1871 } ] }

Second Stage

The $match stage filters the output from the previous stage to only return buckets which contain more than 3 documents.

The operation returns the following document:

{ "_id" : 1860, "count" : 4, "artists" :
  [
    { "name" : "Emil Bernard", "year_born" : 1868 },
    { "name" : "Joszef Rippl-Ronai", "year_born" : 1861 },
    { "name" : "Alfred Maurer", "year_born" : 1868 },
    { "name" : "Edvard Munch", "year_born" : 1863 }
  ]
}

Use $bucket with $facet to Bucket by Multiple Fields

You can use the $facet stage to perform multiple $bucket aggregations in a single stage.

In mongosh, create a sample collection named artwork with the following documents:

db.artwork.insertMany([
  { "_id" : 1, "title" : "The Pillars of Society", "artist" : "Grosz", "year" : 1926,
      "price" : NumberDecimal("199.99") },
  { "_id" : 2, "title" : "Melancholy III", "artist" : "Munch", "year" : 1902,
      "price" : NumberDecimal("280.00") },
  { "_id" : 3, "title" : "Dancer", "artist" : "Miro", "year" : 1925,
      "price" : NumberDecimal("76.04") },
  { "_id" : 4, "title" : "The Great Wave off Kanagawa", "artist" : "Hokusai",
      "price" : NumberDecimal("167.30") },
  { "_id" : 5, "title" : "The Persistence of Memory", "artist" : "Dali", "year" : 1931,
      "price" : NumberDecimal("483.00") },
  { "_id" : 6, "title" : "Composition VII", "artist" : "Kandinsky", "year" : 1913,
      "price" : NumberDecimal("385.00") },
  { "_id" : 7, "title" : "The Scream", "artist" : "Munch", "year" : 1893
      /* No price*/ },
  { "_id" : 8, "title" : "Blue Flower", "artist" : "O'Keefe", "year" : 1918,
      "price" : NumberDecimal("118.42") }
])

The following operation uses two $bucket stages within a $facet stage to create two groupings, one by price and the other by year:

db.artwork.aggregate( [
  {
    $facet: {                               // Top-level $facet stage
      "price": [                            // Output field 1
        {
          $bucket: {
              groupBy: "$price",            // Field to group by
              boundaries: [ 0, 200, 400 ],  // Boundaries for the buckets
              default: "Other",             // Bucket ID for documents which do not fall into a bucket
              output: {                     // Output for each bucket
                "count": { $sum: 1 },
                "artwork" : { $push: { "title": "$title", "price": "$price" } },
                "averagePrice": { $avg: "$price" }
              }
          }
        }
      ],
      "year": [                                      // Output field 2
        {
          $bucket: {
            groupBy: "$year",                        // Field to group by
            boundaries: [ 1890, 1910, 1920, 1940 ],  // Boundaries for the buckets
            default: "Unknown",                      // Bucket ID for documents which do not fall into a bucket
            output: {                                // Output for each bucket
              "count": { $sum: 1 },
              "artwork": { $push: { "title": "$title", "year": "$year" } }
            }
          }
        }
      ]
    }
  }
] )

First Facet

The first facet groups the input documents by price. The buckets have the following boundaries:

• [0, 200) with inclusive lowerbound 0 and exclusive upper bound 200.

• [200, 400) with inclusive lowerbound 200 and exclusive upper bound 400.

• "Other", the default bucket containing documents without prices or prices outside the ranges above.

The $bucket stage includes the output document to determine the fields to return:

Field	Description
_id	Inclusive lower bound of the bucket.
count	Count of documents in the bucket.
artwork	Array of documents containing information on each artwork in the bucket.
averagePrice	Employs the $avg operator to display the average price of all artwork in the bucket.

Second Facet

The second facet groups the input documents by year. The buckets have the following boundaries:

• [1890, 1910) with inclusive lowerbound 1890 and exclusive upper bound 1910.

• [1910, 1920) with inclusive lowerbound 1910 and exclusive upper bound 1920.

• [1920, 1940) with inclusive lowerbound 1910 and exclusive upper bound 1940.

• "Unknown", the default bucket containing documents without years or years outside the ranges above.

The $bucket stage includes the output document to determine the fields to return:

Field	Description
count	Count of documents in the bucket.
artwork	Array of documents containing information on each artwork in the bucket.

Output

The operation returns the following document:

{
  "price" : [ // Output of first facet
    {
      "_id" : 0,
      "count" : 4,
      "artwork" : [
        { "title" : "The Pillars of Society", "price" : NumberDecimal("199.99") },
        { "title" : "Dancer", "price" : NumberDecimal("76.04") },
        { "title" : "The Great Wave off Kanagawa", "price" : NumberDecimal("167.30") },
        { "title" : "Blue Flower", "price" : NumberDecimal("118.42") }
      ],
      "averagePrice" : NumberDecimal("140.4375")
    },
    {
      "_id" : 200,
      "count" : 2,
      "artwork" : [
        { "title" : "Melancholy III", "price" : NumberDecimal("280.00") },
        { "title" : "Composition VII", "price" : NumberDecimal("385.00") }
      ],
      "averagePrice" : NumberDecimal("332.50")
    },
    {
      // Includes documents without prices and prices greater than 400
      "_id" : "Other",
      "count" : 2,
      "artwork" : [
        { "title" : "The Persistence of Memory", "price" : NumberDecimal("483.00") },
        { "title" : "The Scream" }
      ],
      "averagePrice" : NumberDecimal("483.00")
    }
  ],
  "year" : [ // Output of second facet
    {
      "_id" : 1890,
      "count" : 2,
      "artwork" : [
        { "title" : "Melancholy III", "year" : 1902 },
        { "title" : "The Scream", "year" : 1893 }
      ]
    },
    {
      "_id" : 1910,
      "count" : 2,
      "artwork" : [
        { "title" : "Composition VII", "year" : 1913 },
        { "title" : "Blue Flower", "year" : 1918 }
      ]
    },
    {
      "_id" : 1920,
      "count" : 3,
      "artwork" : [
        { "title" : "The Pillars of Society", "year" : 1926 },
        { "title" : "Dancer", "year" : 1925 },
        { "title" : "The Persistence of Memory", "year" : 1931 }
      ]
    },
    {
      // Includes documents without a year
      "_id" : "Unknown",
      "count" : 1,
      "artwork" : [
        { "title" : "The Great Wave off Kanagawa" }
      ]
    }
  ]
}