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mongodb Aggregation聚合操作之$bucket

mongodb Aggregation聚合操作之$bucket

作者: 蚁族的乐土 | 来源:发表于2021-03-18 19:13 被阅读0次

    在上一篇mongodb Aggregation聚合操作之$facet中详细介绍了mongodb聚合操作中的$facet使用以及参数细节。本篇将开始介绍Aggregation聚合操作中的$bucket操作。

    说明:

    根据指定的表达式和bucket边界将传入的文档分类到称为bucket的组中,并为每个bucket输出一个文档。每个输出文档都包含一个_id字段,其值指定bucket的包含下界。输出选项指定每个输出文档中包含的字段。

    $bucket只为至少包含一个输入文档的bucket生成输出文档。

    语法:

    {

      $bucket: {

          groupBy: <expression>,

          boundaries: [ <lowerbound1>, <lowerbound2>, ... ],

          default: <literal>,

          output: {

             <output1>: { <$accumulator expression> },

             ...

             <outputN>: { <$accumulator expression> }

          }

       }

    }

    参数讲解:

    groupBy:用来对文档进行分组的表达式。要指定字段路径,请在字段名称前加上美元符号$并将其括在引号中。除非$bucket包含默认规范,否则每个输入文档必须将groupBy字段路径或表达式解析为属于边界指定的范围之一的值。

    boundaries:一个基于groupBy表达式的值数组,该表达式指定每个bucket的边界。每一对相邻的值充当桶的包含下边界和独占上边界。您必须指定至少两个边界。

    default:可选的。指定附加bucket的_id的文字,该bucket包含groupBy表达式结果不属于边界指定的bucket的所有文档。如果未指定,则每个输入文档必须将groupBy表达式解析为由边界指定的bucket范围中的一个值,否则操作将抛出错误。默认值必须小于最低边界值,或大于或等于最高边界值。

    默认值可以是与边界项不同的类型。

    output:可选的。除_id字段外,指定输出文档中要包含的字段的文档。要指定要包含的字段,必须使用累加器表达式。

    1. 示例

    1.1. 单bucket示例

    初始化数据:

    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" }

    ])

    示例:

    db.artists.aggregate( [

      // First Stage

      {

        $bucket: {

          groupBy: "$year_born",  // 按year_born字段分组

          boundaries: [ 1840, 1850, 1860, 1870, 1880 ], // 桶的边界

          default: "Other",  // 不属于Bucket的文档的Bucket id【如果一个文档不包含year_born字段,或者它的year_born字段在上面的范围之外,那么它将被放在_id值为“Other”的默认bucket中。】

          output: {  //输出

            "count": { $sum: 1 },

            "artists" :

              {

                $push: {

                  "name": { $concat: [ "$first_name", " ", "$last_name"] },

                  "year_born": "$year_born"

                }

              }

          }

        }

      },

      // 筛选结果大于3的

      {

        $match: { count: {$gt: 3} }

      }

    ] )

    结果是:

    {

        "_id" : 1860.0, //桶的包含下界。

        "count" : 4.0,//桶中文档的计数。

        "artists" : [ //包含bucket中每个艺术家信息的文档数组。每个文档都包含了艺术家的name,它是艺术家的first_name和last_name的连接(即$concat)

            {

                "name" : "Emil Bernard",

                "year_born" : 1868.0

            },

            {

                "name" : "Joszef Rippl-Ronai",

                "year_born" : 1861.0

            },

            {

                "name" : "Alfred Maurer",

                "year_born" : 1868.0

            },

            {

                "name" : "Edvard Munch",

                "year_born" : 1863.0

            }

        ]

    }

    1.2. 使用带有$facet的$bucket,通过多个字段实现bucket

    可以使用$facet阶段在单个阶段中执行多个$bucket聚合。

    初始化数据:

    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") }

    ])

    示例:下面的操作使用$facet阶段中的两个$bucket阶段创建两个分组,一个按价格,另一个按年:

    db.artwork.aggregate( [

      {

        $facet: {    // 顶级$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" } }

                }

              }

            }

          ]

        }

      }

    ] )

    结果:

    [ { price:

         [ { _id: 0,

             count: 4,

             artwork:

              [ { title: 'The Pillars of Society',

                  price:

                   { _bsontype: 'Decimal128',

                     bytes: <Buffer 1f 4e 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } },

                { title: 'Dancer',

                  price:

                   { _bsontype: 'Decimal128',

                     bytes: <Buffer b4 1d 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } },

                { title: 'The Great Wave off Kanagawa',

                  price:

                   { _bsontype: 'Decimal128',

                     bytes: <Buffer 5a 41 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } },

                { title: 'Blue Flower',

                  price:

                   { _bsontype: 'Decimal128',

                     bytes: <Buffer 42 2e 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } } ],

             averagePrice:

              { _bsontype: 'Decimal128',

                bytes: <Buffer d7 6d 15 00 00 00 00 00 00 00 00 00 00 00 38 30> } },

           { _id: 200,

             count: 2,

             artwork:

              [ { title: 'Melancholy III',

                  price:

                   { _bsontype: 'Decimal128',

                     bytes: <Buffer 60 6d 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } },

                { title: 'Composition VII',

                  price:

                   { _bsontype: 'Decimal128',

                     bytes: <Buffer 64 96 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } } ],

             averagePrice:

              { _bsontype: 'Decimal128',

                bytes: <Buffer e2 81 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } },

           { _id: 'Other',

             count: 2,

             artwork:

              [ { title: 'The Persistence of Memory',

                  price:

                   { _bsontype: 'Decimal128',

                     bytes: <Buffer ac bc 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } },

                { title: 'The Scream' } ],

             averagePrice:

              { _bsontype: 'Decimal128',

                bytes: <Buffer ac bc 00 00 00 00 00 00 00 00 00 00 00 00 3c 30> } } ],

        year:

         [ { _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 } ] },

           { _id: 'Unknown',

             count: 1,

             artwork: [ { title: 'The Great Wave off Kanagawa' } ] } ] } ]

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