运行聚合管道

本页内容

理解聚合语法

示例

您可以使用聚合管道在您的集合中使用MongoDB Shell. 聚合管道根据选择的管道阶段将文档转换为聚合结果。

聚合的常见用途包括

按给定表达式对数据进行分组。
根据多个字段计算结果，并将这些结果存储在新字段中。
过滤数据以返回匹配给定标准的子集。
排序数据。

当您运行聚合时，MongoDB Shell将结果直接输出到终端。

理解聚合语法

MongoDB聚合管道由阶段组成。每个阶段都会在文档通过管道时对其进行转换。管道阶段不需要为每个输入文档产生一个输出文档；例如，某些阶段可能生成新文档或过滤掉文档。

要创建一个聚合管道，请使用以下语法在MongoDB Shell:

1 db.<collection>.aggregate([
2   {
3     <$stage1>
4   },
5   {
6     <$stage2>
7   }
8   ...
9 ])

示例

本页上的示例引用了Atlas 示例数据集。您可以创建一个免费的Atlas集群，并将示例数据填充到该集群中，以跟随这些示例。有关更多信息，请参阅Atlas入门。

下面的示例使用了movies 集合中的Atlas sample_mflix 示例数据集。

示例文档

电影集合中的每个文档都描述了一部电影

1 {
2   _id: 573a1397f29313caabce8347,
3   fullplot: 'In a cyberpunk vision of the future, man has developed the technology to create replicants, human clones used to serve in the colonies outside Earth but with fixed lifespans. In Los Angeles, 2019, Deckard is a Blade Runner, a cop who specializes in terminating replicants. Originally in retirement, he is forced to re-enter the force when four replicants escape from an off-world colony to Earth.',
4   imdb: { rating: 8.2, votes: 419589, id: 83658 },
5   year: 1982,
6   plot: 'A blade runner must pursue and try to terminate four replicants who stole a ship in space and have returned to Earth to find their creator.',
7   genres: [ 'Sci-Fi', 'Thriller' ],
8   rated: 'R',
9   metacritic: 88,
10   title: 'Blade Runner',
11   lastupdated: '2015-09-04 00:05:51.990000000',
12   languages: [ 'English', 'German', 'Cantonese', 'Japanese', 'Hungarian' ],
13   writers: [
14     'Hampton Fancher (screenplay)',
15     'David Webb Peoples (screenplay)',
16     'Philip K. Dick (novel)'
17   ],
18   type: 'movie',
19   tomatoes: {
20     viewer: { rating: 4, numReviews: 331213, meter: 91 },
21     dvd: 1997-08-27T00:00:00.000Z,
22     critic: { rating: 8.5, numReviews: 102, meter: 90 },
23     lastUpdated: 2015-09-12T17:48:21.000Z,
24     consensus: "Misunderstood when it first hit theaters, the influence of Ridley Scott's mysterious, neo-noir Blade Runner has deepened with time. A visually remarkable, achingly human sci-fi masterpiece.",
25     rotten: 10,
26     production: 'Warner Bros. Pictures',
27     fresh: 92
28   },
29   poster: 'https://m.media-amazon.com/images/M/MV5BNzQzMzJhZTEtOWM4NS00MTdhLTg0YjgtMjM4MDRkZjUwZDBlXkEyXkFqcGdeQXVyNjU0OTQ0OTY@._V1_SY1000_SX677_AL_.jpg',
30   num_mflix_comments: 1,
31   released: 1982-06-25T00:00:00.000Z,
32   awards: {
33     wins: 13,
34     nominations: 15,
35     text: 'Nominated for 2 Oscars. Another 11 wins & 15 nominations.'
36   },
37   countries: [ 'USA', 'Hong Kong', 'UK' ],
38   cast: [
39     'Harrison Ford',
40     'Rutger Hauer',
41     'Sean Young',
42     'Edward James Olmos'
43   ],
44   directors: [ 'Ridley Scott' ],
45   runtime: 117
46 }

本教程中聚合的文档位于 sample_mflix.movies 集合中。使用以下命令切换到包含此集合的数据库

use sample_mflix

示例聚合管道

考虑以下管道

1 db.movies.aggregate([
2 
3   // First Stage
4 
5   { $project: { _id: 0, genres: 1, imdb: 1, title: 1 } },
6 
7   // Second Stage
8 
9   { $unwind: "$genres" },
10 
11   // Third Stage
12 
13   { $group:
14     { _id: "$genres",
15       averageGenreRating: { $avg: "$imdb.rating" }
16     }
17   },
18 
19    // Fourth Stage
20 
21    { $sort: { averageGenreRating: -1 } }
22 ] )

此管道在四个阶段进行聚合

第一阶段

$project 阶段将包含以下字段的文档传递到下一个管道阶段

genres
imdb
title

不包含所有这些字段的集合文档不会被传递到下一个管道阶段。

注意

在 $project 阶段中指定 _id: 0 以抑制传递给下一个阶段的文档中的 _id 字段。

有关更多信息，请参阅 MongoDB 手册。

$project 阶段转换示例文档，并将以下输出传递到下一个管道阶段

1 {
2   imdb: { rating: 8.2, votes: 419589, id: 83658 },
3   genres: [ 'Sci-Fi', 'Thriller' ],
4   title: 'Blade Runner'
5 }

第二阶段

$unwind 阶段将 genres 数组中的每个元素传递到下一个管道阶段。

《$unwind》阶段从原始示例文档中生成以下两个文档，然后将它们传递给下一个管道阶段：

1 {
2   imdb: { rating: 8.2, votes: 419589, id: 83658 },
3   genres: 'Sci-Fi',
4   title: 'Blade Runner'
5 }

1 {
2   imdb: { rating: 8.2, votes: 419589, id: 83658 },
3   genres: 'Thriller',
4   title: 'Blade Runner'
5 }

第三阶段

《$group》阶段

从上一个管道阶段接收到的文档中检索不同的类型值，
为每个不同的类型创建一个文档，其中_id是类型名称，
在每个新文档中添加一个字段averageGenreRating，它包含所有匹配类型的文档的平均imdb.rating，并且
将新文档传递给下一个管道阶段。

此阶段将类似于以下文档发送到下一个管道阶段

1 { _id: 'Sport', averageGenreRating: 6.781233933161954 },
2 { _id: 'History', averageGenreRating: 7.202306920762287 },
3 { _id: 'Biography', averageGenreRating: 7.097142857142857 },
4 { _id: 'Adventure', averageGenreRating: 6.527788649706458 },
5 { _id: 'Family', averageGenreRating: 6.36096256684492 },
6 { _id: 'Crime', averageGenreRating: 6.730478683620045 },
7 { _id: 'Western', averageGenreRating: 6.879197080291971 },
8 { _id: 'Fantasy', averageGenreRating: 6.42495652173913 },
9 { _id: 'Talk-Show', averageGenreRating: 7 },
10 { _id: 'Documentary', averageGenreRating: 7.365266635205286 },
11 { _id: 'War', averageGenreRating: 7.183944374209861 },
12 { _id: 'Short', averageGenreRating: 7.355813953488372 },
13 { _id: 'Horror', averageGenreRating: 5.84110718492344 },
14 { _id: 'Film-Noir', averageGenreRating: 7.503809523809523 },
15 { _id: 'News', averageGenreRating: 7.254901960784314 },
16 { _id: 'Thriller', averageGenreRating: 6.322121555303888 },
17 { _id: 'Action', averageGenreRating: 6.3774842271293375 },
18 { _id: 'Music', averageGenreRating: 6.923452380952381 },
19 { _id: 'Animation', averageGenreRating: 6.917993795243019 },
20 { _id: 'Drama', averageGenreRating: 6.830528688822631 }

第四阶段

《$sort》阶段根据averageGenreRating字段的值按降序对前一阶段接收到的文档进行排序。

运行示例管道后，MongoDB Shell将在终端打印出类似于以下文档

1 [
2   { _id: 'Film-Noir', averageGenreRating: 7.503809523809523 },
3   { _id: 'Documentary', averageGenreRating: 7.365266635205286 },
4   { _id: 'Short', averageGenreRating: 7.355813953488372 },
5   { _id: 'News', averageGenreRating: 7.254901960784314 },
6   { _id: 'History', averageGenreRating: 7.202306920762287 },
7   { _id: 'War', averageGenreRating: 7.183944374209861 },
8   { _id: 'Biography', averageGenreRating: 7.097142857142857 },
9   { _id: 'Talk-Show', averageGenreRating: 7 },
10   { _id: 'Music', averageGenreRating: 6.923452380952381 },
11   { _id: 'Animation', averageGenreRating: 6.917993795243019 },
12   { _id: 'Western', averageGenreRating: 6.879197080291971 },
13   { _id: 'Drama', averageGenreRating: 6.830528688822631 },
14   { _id: 'Sport', averageGenreRating: 6.781233933161954 },
15   { _id: 'Crime', averageGenreRating: 6.730478683620045 },
16   { _id: 'Musical', averageGenreRating: 6.696913580246913 },
17   { _id: 'Romance', averageGenreRating: 6.695711554220159 },
18   { _id: 'Mystery', averageGenreRating: 6.563317384370015 },
19   { _id: 'Adventure', averageGenreRating: 6.527788649706458 },
20   { _id: 'Comedy', averageGenreRating: 6.479626461362988 },
21   { _id: 'Fantasy', averageGenreRating: 6.42495652173913 }
22 ]

提示

另请参阅

要了解有关可用聚合阶段的更多信息，请参阅聚合管道阶段。
要了解有关可用聚合运算符的更多信息，您可以在阶段中使用，请参阅聚合管道运算符。

删除

下一步

客户端字段级加密

1	db.<collection>.aggregate([
2	{
3	<$stage1>
4	},
5	{
6	<$stage2>
7	}
8	...
9	])

1	{
2	_id: 573a1397f29313caabce8347,
3	fullplot: 'In a cyberpunk vision of the future, man has developed the technology to create replicants, human clones used to serve in the colonies outside Earth but with fixed lifespans. In Los Angeles, 2019, Deckard is a Blade Runner, a cop who specializes in terminating replicants. Originally in retirement, he is forced to re-enter the force when four replicants escape from an off-world colony to Earth.',
4	imdb: { rating: 8.2, votes: 419589, id: 83658 },
5	year: 1982,
6	plot: 'A blade runner must pursue and try to terminate four replicants who stole a ship in space and have returned to Earth to find their creator.',
7	genres: [ 'Sci-Fi', 'Thriller' ],
8	rated: 'R',
9	metacritic: 88,
10	title: 'Blade Runner',
11	lastupdated: '2015-09-04 00:05:51.990000000',
12	languages: [ 'English', 'German', 'Cantonese', 'Japanese', 'Hungarian' ],
13	writers: [
14	'Hampton Fancher (screenplay)',
15	'David Webb Peoples (screenplay)',
16	'Philip K. Dick (novel)'
17	],
18	type: 'movie',
19	tomatoes: {
20	viewer: { rating: 4, numReviews: 331213, meter: 91 },
21	dvd: 1997-08-27T00:00:00.000Z,
22	critic: { rating: 8.5, numReviews: 102, meter: 90 },
23	lastUpdated: 2015-09-12T17:48:21.000Z,
24	consensus: "Misunderstood when it first hit theaters, the influence of Ridley Scott's mysterious, neo-noir Blade Runner has deepened with time. A visually remarkable, achingly human sci-fi masterpiece.",
25	rotten: 10,
26	production: 'Warner Bros. Pictures',
27	fresh: 92
28	},
29	poster: 'https://m.media-amazon.com/images/M/MV5BNzQzMzJhZTEtOWM4NS00MTdhLTg0YjgtMjM4MDRkZjUwZDBlXkEyXkFqcGdeQXVyNjU0OTQ0OTY@._V1_SY1000_SX677_AL_.jpg',
30	num_mflix_comments: 1,
31	released: 1982-06-25T00:00:00.000Z,
32	awards: {
33	wins: 13,
34	nominations: 15,
35	text: 'Nominated for 2 Oscars. Another 11 wins & 15 nominations.'
36	},
37	countries: [ 'USA', 'Hong Kong', 'UK' ],
38	cast: [
39	'Harrison Ford',
40	'Rutger Hauer',
41	'Sean Young',
42	'Edward James Olmos'
43	],
44	directors: [ 'Ridley Scott' ],
45	runtime: 117
46	}

1	db.movies.aggregate([
2
3	// First Stage
4
5	{ $project: { _id: 0, genres: 1, imdb: 1, title: 1 } },
6
7	// Second Stage
8
9	{ $unwind: "$genres" },
10
11	// Third Stage
12
13	{ $group:
14	{ _id: "$genres",
15	averageGenreRating: { $avg: "$imdb.rating" }
16	}
17	},
18
19	// Fourth Stage
20
21	{ $sort: { averageGenreRating: -1 } }
22	] )

1	{
2	imdb: { rating: 8.2, votes: 419589, id: 83658 },
3	genres: [ 'Sci-Fi', 'Thriller' ],
4	title: 'Blade Runner'
5	}

1	{
2	imdb: { rating: 8.2, votes: 419589, id: 83658 },
3	genres: 'Sci-Fi',
4	title: 'Blade Runner'
5	}

1	{
2	imdb: { rating: 8.2, votes: 419589, id: 83658 },
3	genres: 'Thriller',
4	title: 'Blade Runner'
5	}

1	{ _id: 'Sport', averageGenreRating: 6.781233933161954 },
2	{ _id: 'History', averageGenreRating: 7.202306920762287 },
3	{ _id: 'Biography', averageGenreRating: 7.097142857142857 },
4	{ _id: 'Adventure', averageGenreRating: 6.527788649706458 },
5	{ _id: 'Family', averageGenreRating: 6.36096256684492 },
6	{ _id: 'Crime', averageGenreRating: 6.730478683620045 },
7	{ _id: 'Western', averageGenreRating: 6.879197080291971 },
8	{ _id: 'Fantasy', averageGenreRating: 6.42495652173913 },
9	{ _id: 'Talk-Show', averageGenreRating: 7 },
10	{ _id: 'Documentary', averageGenreRating: 7.365266635205286 },
11	{ _id: 'War', averageGenreRating: 7.183944374209861 },
12	{ _id: 'Short', averageGenreRating: 7.355813953488372 },
13	{ _id: 'Horror', averageGenreRating: 5.84110718492344 },
14	{ _id: 'Film-Noir', averageGenreRating: 7.503809523809523 },
15	{ _id: 'News', averageGenreRating: 7.254901960784314 },
16	{ _id: 'Thriller', averageGenreRating: 6.322121555303888 },
17	{ _id: 'Action', averageGenreRating: 6.3774842271293375 },
18	{ _id: 'Music', averageGenreRating: 6.923452380952381 },
19	{ _id: 'Animation', averageGenreRating: 6.917993795243019 },
20	{ _id: 'Drama', averageGenreRating: 6.830528688822631 }