$bucket (aggregation)¶

Bucket by Year and Filter by Bucket Results每年一桶，按桶筛选结果¶

From the mongo shell, create a sample collection named artists with the following documents:从mongo shell中，创建一个名为artists的样本集合，并附带以下文档：

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:以下操作根据year_born字段将文档分组到存储桶中，并根据存储桶中的文档计数进行筛选：

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第一阶段

The $bucket stage groups the documents into buckets by the year_born field. $bucket阶段按year_born字段将文档分组到存储桶中。The buckets have the following boundaries:存储桶具有以下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:该阶段包括输出文档，用于确定要返回的字段：

_id	Inclusive lower bound of the bucket.包含桶的下限。
count	Count of documents in the bucket.清点桶里的文件。
artists	Array of documents containing information on each artist in the bucket. 包含桶中每个艺术家信息的文档数组。Each document contains the artist’s每个文档都包含艺术家的 name, which is a concatenation (i.e. $concat) of the artist’s first_name and last_name.name，是艺术家的名字和姓氏的串联（即$concat）。 year_born

This stage passes the following documents to the next stage:本阶段将以下文件传递到下一阶段：

{ "_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第二阶段

The $match stage filters the output from the previous stage to only return buckets which contain more than 3 documents.$match阶段筛选前一阶段的输出，只返回包含3个以上文档的存储桶。

The operation returns the following document:该操作将返回以下文档：

{ "_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 $facet to Bucket by Multiple Fields通过多个字段对存储桶使用$bucket和$facet¶

You can use the $facet stage to perform multiple $bucket aggregations in a single stage.可以使用$facet阶段在单个阶段中执行多个$bucket聚合。

From the mongo shell, create a sample collection named artwork with the following documents:在mongo shell中，创建一个名为artwork的样本集合，其中包含以下文档：

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 $facet stage to create two groupings, one by price and the other by year:以下操作使用$facet阶段中的两个$bucket阶段创建两个分组，一个按price，另一个按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. 第一个方面按price对输入文档进行分组。The buckets have the following boundaries:铲斗具有以下边界：

• [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:

_id	Inclusive lower bound of the bucket.包含桶的下限。
count	Count of documents in the bucket.清点桶里的文件。
artwork	Array of documents containing information on each artwork in the bucket.包含桶中每个艺术品信息的文档数组。
averagePrice	Employs the $avg operator to display the average price of all artwork in the bucket.雇佣$avg运算符显示桶中所有艺术品的平均价格。

Second Facet第二方面

The second facet groups the input documents by year. 第二个方面按year对输入文档进行分组。The buckets have the following boundaries:铲斗具有以下边界：

• [1890, 1910) with inclusive lowerbound 1890 and exclusive upper bound 1910.具有包括1890年的下限和排除1910年的上限。
• [1910, 1920) with inclusive lowerbound 1910 and exclusive upper bound 1920.具有包括1910年的下限和排除1920年的上限。
• [1920, 1940) with inclusive lowerbound 1910 and exclusive upper bound 1940.具有包括1910年的下限和排除1940年的上限。
• “Unknown”, the default bucket containing documents without years or years outside the ranges above.“Unknown”，default存储桶中包含的文档没有年份或年份超出上述范围。

The $bucket stage includes the output document to determine the fields to return:$bucket阶段包括用于确定要返回的字段的输出文档：

count	Count of documents in the bucket.清点桶里的文件。
artwork	Array of documents containing information on each artwork in the bucket.包含桶中每个艺术品信息的文档数组。

Output

The operation returns the following document:该操作将返回以下文档：

{
  "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" }
      ]
    }
  ]
}