mongodb按多个字段分组值

tp5buhyn  于 2022-12-12  发布在  Go
关注(0)|答案(4)|浏览(168)

例如，我有以下文档：

{
  "addr": "address1",
  "book": "book1"
},
{
  "addr": "address2",
  "book": "book1"
},
{
  "addr": "address1",
  "book": "book5"
},
{
  "addr": "address3",
  "book": "book9"
},
{
  "addr": "address2",
  "book": "book5"
},
{
  "addr": "address2",
  "book": "book1"
},
{
  "addr": "address1",
  "book": "book1"
},
{
  "addr": "address15",
  "book": "book1"
},
{
  "addr": "address9",
  "book": "book99"
},
{
  "addr": "address90",
  "book": "book33"
},
{
  "addr": "address4",
  "book": "book3"
},
{
  "addr": "address5",
  "book": "book1"
},
{
  "addr": "address77",
  "book": "book11"
},
{
  "addr": "address1",
  "book": "book1"
}

和/或其他信息。
我如何才能提出一个请求，该请求将描述前N个地址和每个地址的前M本书？
预期结果示例：
地址1|书册_1：5
| 书册_2：10
| 书籍_3：50
| 总数：65

地址2|书册_1：10
| 书册_2：10
|...
| 书本_M：10
| 总计：M*10
...

地址N|书册_1：20
| 书册_2：20
|...
| 书本_M：20
| 总计：M*20

mongodb

4条答案

按热度按时间
rryofs0p

rryofs0p1#

TLDR摘要

在现代的MongoDB版本中，您可以使用$slice来强制执行此操作，而不是基本的聚合结果。对于“大型”结果，可以对每个分组运行并行查询（答案末尾有一个演示列表），或者等待SERVER-9377解析，这将允许将数组中的项的数量“限制”为$push。

db.books.aggregate([
    { "$group": {
        "_id": {
            "addr": "$addr",
            "book": "$book"
        },
        "bookCount": { "$sum": 1 }
    }},
    { "$group": {
        "_id": "$_id.addr",
        "books": { 
            "$push": { 
                "book": "$_id.book",
                "count": "$bookCount"
            },
        },
        "count": { "$sum": "$bookCount" }
    }},
    { "$sort": { "count": -1 } },
    { "$limit": 2 },
    { "$project": {
        "books": { "$slice": [ "$books", 2 ] },
        "count": 1
    }}
])

MongoDB 3.6预览版
仍然无法解析SERVER-9377，但在此版本中$lookup允许一个新的“非相关”选项，该选项将"pipeline"表达式作为参数，而不是"localFields"和"foreignFields"选项。这允许与另一个管道表达式进行“自连接”，在该管道表达式中，我们可以应用$limit以返回“top-n”结果。

db.books.aggregate([
  { "$group": {
    "_id": "$addr",
    "count": { "$sum": 1 }
  }},
  { "$sort": { "count": -1 } },
  { "$limit": 2 },
  { "$lookup": {
    "from": "books",
    "let": {
      "addr": "$_id"
    },
    "pipeline": [
      { "$match": { 
        "$expr": { "$eq": [ "$addr", "$$addr"] }
      }},
      { "$group": {
        "_id": "$book",
        "count": { "$sum": 1 }
      }},
      { "$sort": { "count": -1  } },
      { "$limit": 2 }
    ],
    "as": "books"
  }}
])

这里的另一个附加功能当然是使用$match通过$expr插入变量以选择“join”中的匹配项，但一般前提是“管道中的管道”，其中内部内容可以通过来自父级的匹配进行过滤。由于它们本身都是“管道”，我们可以分别对每个结果进行$limit。
这将是运行并行查询的次佳选择，实际上，如果允许$match并能够在“子管道”处理中使用索引，这将更好。因此，它没有像引用的问题所要求的那样使用“限制为$push“，它实际上提供了一些应该工作得更好的东西。

原始内容

你似乎无意中发现了前N个问题。从某种程度上说，你的问题很容易解决，尽管没有你要求的确切限制：

db.books.aggregate([
    { "$group": {
        "_id": {
            "addr": "$addr",
            "book": "$book"
        },
        "bookCount": { "$sum": 1 }
    }},
    { "$group": {
        "_id": "$_id.addr",
        "books": { 
            "$push": { 
                "book": "$_id.book",
                "count": "$bookCount"
            },
        },
        "count": { "$sum": "$bookCount" }
    }},
    { "$sort": { "count": -1 } },
    { "$limit": 2 }
])

既然会给予你这样一个结果：

{
    "result" : [
            {
                    "_id" : "address1",
                    "books" : [
                            {
                                    "book" : "book4",
                                    "count" : 1
                            },
                            {
                                    "book" : "book5",
                                    "count" : 1
                            },
                            {
                                    "book" : "book1",
                                    "count" : 3
                            }
                    ],
                    "count" : 5
            },
            {
                    "_id" : "address2",
                    "books" : [
                            {
                                    "book" : "book5",
                                    "count" : 1
                            },
                            {
                                    "book" : "book1",
                                    "count" : 2
                            }
                    ],
                    "count" : 3
            }
    ],
    "ok" : 1
}

因此，这与您所要求的不同之处在于，虽然我们确实获得了地址值的最佳结果，但基础“books”选择并不限于所需数量的结果。
这是很难做到的，但它可以做到，虽然复杂性只会随着你需要匹配的项目的数量而增加。为了保持简单，我们可以保持最多2个匹配：

db.books.aggregate([
    { "$group": {
        "_id": {
            "addr": "$addr",
            "book": "$book"
        },
        "bookCount": { "$sum": 1 }
    }},
    { "$group": {
        "_id": "$_id.addr",
        "books": { 
            "$push": { 
                "book": "$_id.book",
                "count": "$bookCount"
            },
        },
        "count": { "$sum": "$bookCount" }
    }},
    { "$sort": { "count": -1 } },
    { "$limit": 2 },
    { "$unwind": "$books" },
    { "$sort": { "count": 1, "books.count": -1 } },
    { "$group": {
        "_id": "$_id",
        "books": { "$push": "$books" },
        "count": { "$first": "$count" }
    }},
    { "$project": {
        "_id": {
            "_id": "$_id",
            "books": "$books",
            "count": "$count"
        },
        "newBooks": "$books"
    }},
    { "$unwind": "$newBooks" },
    { "$group": {
      "_id": "$_id",
      "num1": { "$first": "$newBooks" }
    }},
    { "$project": {
        "_id": "$_id",
        "newBooks": "$_id.books",
        "num1": 1
    }},
    { "$unwind": "$newBooks" },
    { "$project": {
        "_id": "$_id",
        "num1": 1,
        "newBooks": 1,
        "seen": { "$eq": [
            "$num1",
            "$newBooks"
        ]}
    }},
    { "$match": { "seen": false } },
    { "$group":{
        "_id": "$_id._id",
        "num1": { "$first": "$num1" },
        "num2": { "$first": "$newBooks" },
        "count": { "$first": "$_id.count" }
    }},
    { "$project": {
        "num1": 1,
        "num2": 1,
        "count": 1,
        "type": { "$cond": [ 1, [true,false],0 ] }
    }},
    { "$unwind": "$type" },
    { "$project": {
        "books": { "$cond": [
            "$type",
            "$num1",
            "$num2"
        ]},
        "count": 1
    }},
    { "$group": {
        "_id": "$_id",
        "count": { "$first": "$count" },
        "books": { "$push": "$books" }
    }},
    { "$sort": { "count": -1 } }
])

因此，这实际上会从前两个“地址”条目中为您提供前两个“书籍”。
但是对于我的钱，停留在第一个形式，然后简单地“切片”返回的数组元素，以采取前“N”个元素。

演示代码

演示代码适用于当前LTS版本的NodeJS（从v8.x到v10.x）。这主要是针对async/await语法，但在一般流程中没有任何真正具有此类限制的内容，只需稍加修改即可适应普通的承诺，甚至返回到普通的回调实现。

索引.js

const { MongoClient } = require('mongodb');
const fs = require('mz/fs');

const uri = 'mongodb://localhost:27017';

const log = data => console.log(JSON.stringify(data, undefined, 2));

(async function() {

  try {
    const client = await MongoClient.connect(uri);

    const db = client.db('bookDemo');
    const books = db.collection('books');

    let { version } = await db.command({ buildInfo: 1 });
    version = parseFloat(version.match(new RegExp(/(?:(?!-).)*/))[0]);

    // Clear and load books
    await books.deleteMany({});

    await books.insertMany(
      (await fs.readFile('books.json'))
        .toString()
        .replace(/\n$/,"")
        .split("\n")
        .map(JSON.parse)
    );

    if ( version >= 3.6 ) {

    // Non-correlated pipeline with limits
      let result = await books.aggregate([
        { "$group": {
          "_id": "$addr",
          "count": { "$sum": 1 }
        }},
        { "$sort": { "count": -1 } },
        { "$limit": 2 },
        { "$lookup": {
          "from": "books",
          "as": "books",
          "let": { "addr": "$_id" },
          "pipeline": [
            { "$match": {
              "$expr": { "$eq": [ "$addr", "$$addr" ] }
            }},
            { "$group": {
              "_id": "$book",
              "count": { "$sum": 1 },
            }},
            { "$sort": { "count": -1 } },
            { "$limit": 2 }
          ]
        }}
      ]).toArray();

      log({ result });
    }

    // Serial result procesing with parallel fetch

    // First get top addr items
    let topaddr = await books.aggregate([
      { "$group": {
        "_id": "$addr",
        "count": { "$sum": 1 }
      }},
      { "$sort": { "count": -1 } },
      { "$limit": 2 }
    ]).toArray();

    // Run parallel top books for each addr
    let topbooks = await Promise.all(
      topaddr.map(({ _id: addr }) =>
        books.aggregate([
          { "$match": { addr } },
          { "$group": {
            "_id": "$book",
            "count": { "$sum": 1 }
          }},
          { "$sort": { "count": -1 } },
          { "$limit": 2 }
        ]).toArray()
      )
    );

    // Merge output
    topaddr = topaddr.map((d,i) => ({ ...d, books: topbooks[i] }));
    log({ topaddr });

    client.close();

  } catch(e) {
    console.error(e)
  } finally {
    process.exit()
  }

})()

图书.json

{ "addr": "address1",  "book": "book1"  }
{ "addr": "address2",  "book": "book1"  }
{ "addr": "address1",  "book": "book5"  }
{ "addr": "address3",  "book": "book9"  }
{ "addr": "address2",  "book": "book5"  }
{ "addr": "address2",  "book": "book1"  }
{ "addr": "address1",  "book": "book1"  }
{ "addr": "address15", "book": "book1"  }
{ "addr": "address9",  "book": "book99" }
{ "addr": "address90", "book": "book33" }
{ "addr": "address4",  "book": "book3"  }
{ "addr": "address5",  "book": "book1"  }
{ "addr": "address77", "book": "book11" }
{ "addr": "address1",  "book": "book1"  }
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nkkqxpd9

nkkqxpd92#

使用如下聚合函数：

[
{$group: {_id : {book : '$book',address:'$addr'}, total:{$sum :1}}},
{$project : {book : '$_id.book', address : '$_id.address', total : '$total', _id : 0}}
]

它将给予如下结果：

{
            "total" : 1,
            "book" : "book33",
            "address" : "address90"
        }, 
        {
            "total" : 1,
            "book" : "book5",
            "address" : "address1"
        }, 
        {
            "total" : 1,
            "book" : "book99",
            "address" : "address9"
        }, 
        {
            "total" : 1,
            "book" : "book1",
            "address" : "address5"
        }, 
        {
            "total" : 1,
            "book" : "book5",
            "address" : "address2"
        }, 
        {
            "total" : 1,
            "book" : "book3",
            "address" : "address4"
        }, 
        {
            "total" : 1,
            "book" : "book11",
            "address" : "address77"
        }, 
        {
            "total" : 1,
            "book" : "book9",
            "address" : "address3"
        }, 
        {
            "total" : 1,
            "book" : "book1",
            "address" : "address15"
        }, 
        {
            "total" : 2,
            "book" : "book1",
            "address" : "address2"
        }, 
        {
            "total" : 3,
            "book" : "book1",
            "address" : "address1"
        }

我没有完全得到您期望的结果格式，所以请随意修改为您需要的格式。

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ivqmmu1c

ivqmmu1c3#

以下查询将提供与所需响应中给出的结果完全相同的结果：

db.books.aggregate([
    {
        $group: {
            _id: { addresses: "$addr", books: "$book" },
            num: { $sum :1 }
        }
    },
    {
        $group: {
            _id: "$_id.addresses",
            bookCounts: { $push: { bookName: "$_id.books",count: "$num" } }
        }
    },
    {
        $project: {
            _id: 1,
            bookCounts:1,
            "totalBookAtAddress": {
                "$sum": "$bookCounts.count"
            }
        }
    }

])

响应如下所示：

/* 1 */
{
    "_id" : "address4",
    "bookCounts" : [
        {
            "bookName" : "book3",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 1
},

/* 2 */
{
    "_id" : "address90",
    "bookCounts" : [
        {
            "bookName" : "book33",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 1
},

/* 3 */
{
    "_id" : "address15",
    "bookCounts" : [
        {
            "bookName" : "book1",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 1
},

/* 4 */
{
    "_id" : "address3",
    "bookCounts" : [
        {
            "bookName" : "book9",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 1
},

/* 5 */
{
    "_id" : "address5",
    "bookCounts" : [
        {
            "bookName" : "book1",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 1
},

/* 6 */
{
    "_id" : "address1",
    "bookCounts" : [
        {
            "bookName" : "book1",
            "count" : 3
        },
        {
            "bookName" : "book5",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 4
},

/* 7 */
{
    "_id" : "address2",
    "bookCounts" : [
        {
            "bookName" : "book1",
            "count" : 2
        },
        {
            "bookName" : "book5",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 3
},

/* 8 */
{
    "_id" : "address77",
    "bookCounts" : [
        {
            "bookName" : "book11",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 1
},

/* 9 */
{
    "_id" : "address9",
    "bookCounts" : [
        {
            "bookName" : "book99",
            "count" : 1
        }
    ],
    "totalBookAtAddress" : 1
}
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tpxzln5u

tpxzln5u4#

从mongoDB 3.6版本开始，这就很容易做到了，使用$group、$slice、$limit和$sort：

  1. $group这些书来数它们
  2. $sort，因此稍后将根据计数推送它们
  3. $group乘以address，$push相关书籍，以及$sum每个地址的总数。
  4. $sort按地址总计
  5. $limit地址结果为topN
    1.使用$slice将数组中的图书限制为topM
db.collection.aggregate([
  {$group: {_id: {book: "$book",  addr: "$addr"}, count: {$sum: 1}}},
  {$sort: {"_id.addr": 1, count: -1}},
  {$group: {
      _id: "$_id.addr", totalCount: {$sum: "$count"}, 
      books: {$push: {book: "$_id.book", count: "$count"}}
    }
  },
  {$sort: {totalCount: -1}},
  {$limit: topN},
  {$set: {addr: "$_id", _id: "$$REMOVE", books: {$slice: ["$books", 0, topM]}}}
])

了解它在playground example-v3.4上的工作原理
在mongoDB版本5.2上，有一个topN累加器，可以简化更多：

db.collection.aggregate([
  {$group: {_id: {book: "$book",  addr: "$addr"}, count: {$sum: 1}}},
  {$group: {
      _id: "$_id.addr",
      totalCount: {$sum: "$count"},
      books: {$topN: {output: {book: "$_id.book", count: "$count"},
                      sortBy: {count: -1},
                      n: topM
      }}
  }},
  {$sort: {totalCount: -1}},
  {$limit: topN},
  {$project: {addr: "$_id", _id: 0, books: 1, totalCount: 1}}
])

了解它在playground example-v5.2上的工作原理

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