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배열 객체 쿼리, 필터링 및 조회

returnScope 옵션을 사용하여 쿼리 의 컨텍스트를 설정하다 하고 객체 배열을 개별 문서로 반환할 수 있습니다.

요구 사항:

returnScope를 사용하여 중첩된 객체를 개별 문서로 조회하려면 다음을 수행해야 합니다.

객체 배열을 embeddedDocuments 유형으로 인덱스합니다.
조회할 중첩 필드에 대해 storedSource를 정의합니다. MongoDB 검색은 storedSource에 정의된 필드만 반환합니다.
쿼리에서 returnStoredSource 옵션을 true로 설정합니다.

구문

returnScope 쿼리에 다음 구문이 있습니다.

{
  $search: {
   "<operator>": {
      <operator-specification>,
   },
   "returnScope": {
      "path": "<embedded-documents-field-to-retrieve>"
   },
   "returnStoredSource": true
  }
}

{
  $searchMeta: {
   "returnScope": {
      "path": "<embedded-documents-field-to-retrieve>"
   },
   "returnStoredSource": true
  },
  "facet": {
    "<operator>": {
      <operator-specification>,
   },
    "facets": {
      <facet-definition>
    }
  }
}

쿼리 구문에 대해 자세히 알아보려면 $search 를 참조하세요.

행동

returnScope 옵션은 쿼리의 검색 컨텍스트를 설정합니다. 쿼리에 returnScope를 지정하면, MongoDB 검색는 각 내장된 문서를 개별 문서처럼 점수화하고, 정렬하며, 개수를 셉니다.

고려 사항

returnScope 옵션을 사용할 때, MongoDB 검색은 embeddedDocument 내에서 storedSource로 구성된 필드만 반환합니다. embeddedDocument 경로 외부의 필드(예: 루트 수준의 필드) 및 storedSource로 설정되지 않은 필드는 반환되지 않습니다.

연산자 사양에서 쿼리 하려는 필드 의 전체 경로를 지정해야 합니다. returnScope 옵션을 사용하는 경우 모든 연산자 사양 경로가 returnScope.path 아래에 중첩되어 있는지 확인해야 합니다. returnScope.path 외부의 필드 쿼리 하려면 hasAncestor 또는 hasRoot 연산자 사용해야 합니다. 자세한 학습 은 다음을 참조하세요.

Retrieve the Root Document ID

When you use returnScope in a query, MongoDB Search populates a searchRootDocumentId metadata field. You can use the searchRootDocumentId metadata field on clusters running MongoDB 8.3 or later. This field contains the identifier of the root document that contains each returned embedded document. To project this value, use the $meta expression with the searchRootDocumentId keyword.

MongoDB Search populates searchRootDocumentId only when your query sets both returnStoredSource: true and returnScope.path. If you reference searchRootDocumentId in a query that does not specify returnScope, the query fails with the following error:

query requires $search root document id metadata, but it is not
available

Use searchRootDocumentId if you want to:

Fetch fields from the parent document after filtering on the child documents.
Group child documents by their parent.

Don't use searchRootDocumentId if:

You need only fields from the matched child documents.
You want to return the parent document for every child document in the result set, since this can be expensive.

예시

다음 예제는 쿼리에서 returnScope 옵션을 사용하는 방법을 보여 줍니다. 이 예제에서는 sample_training.companies 샘플 데이터세트를 사용합니다. 클러스터에 데이터를 로드하고 컬렉션의 필드에 샘플 인덱스를 생성하면, 샘플 데이터에 대해 다음 쿼리를 실행할 수 있습니다.

샘플 인덱스

1 {
2   "mappings": { 
3     "dynamic": false,
4     "fields": { 
5       "funding_rounds": { 
6         "type": "embeddedDocuments",
7         "dynamic": true,
8         "fields": {
9           "investments": {
10             "type": "embeddedDocuments",
11             "dynamic": true
12           }
13         },
14         "storedSource": {
15           "include": [
16             "round_code", 
17             "raised_currency_code",
18             "raised_amount",
19             "investments.person",
20             "investments.financial_org"
21           ] 
22         }
23       } 
24     }
25   }
26 }

위의 인덱스 정의는 MongoDB 검색하다를 다음과 같이 구성합니다.

funding_rounds 및 funding_rounds.investments 필드를 embeddedDocuments 유형으로 인덱싱합니다.
funding_rounds 및 funding_rounds.investments 객체 배열에 중첩된 모든 동적으로 인덱스할 수 있는 필드를 인덱싱합니다.
mongot에 다음 필드를 저장합니다.
- funding_rounds.round_code
- funding_rounds.raised_currency_code
- funding_rounds.raised_amount
- funding_rounds.investments.person
- funding_rounds.investments.financial_org

embeddedDocument 연산자를 사용하여 funding_rounds 및 funding_rounds.investments 필드에서 요소별 쿼리를 수행할 수 있습니다. 다음 섹션에서는 returnScope 옵션을 사용하여 embeddedDocuments 필드를 개별 문서로 조회하는 몇 가지 샘플 쿼리를 보여줍니다.

샘플 문서 구조 from sample_training.companies 컬렉션

{
  ...,
  "funding_rounds": [
    {
      "id": <integer>,
      "round_code": "<string>",
      "source_url": "<string>",
      "source_description": "<string>",
      "raised_amount": <integer>,
      "raised_currency_code": "<string>",
      "funded_year": <integer>,
      "funded_month": "<string>",
      "funded_day": "<string>",
      "investments": [
         {
           "company": "<string>",
           "financial_org": {
             "name": "<string>",
             "permalink": "<string>"
           },
           "person": {
             "first_name": "<string>",
             "last_name": "<string>",
             "permalink": "<string>"
           }
         },
         ...
      ]
    },
    ...
  ],
  ...
}

샘플 쿼리

다음 섹션에서는 returnScope 옵션을 사용하여 mongot에 저장된 embeddedDocuments 유형 필드에서 필드를 조회하는 샘플 쿼리를 보여줍니다.

간단한 쿼리

내장된 문서 필드를 쿼리하고 조회합니다.

다음 range 쿼리(MongoDB 검색 연산자)를 사용하여 funding_rounds.raised_amount 필드 에 이상 및 이하 5000000 및 이하의 금액을 쿼리 10000000. returnScope 옵션을 사용하여 쿼리 범위를 funding_rounds 필드 로 설정합니다. returnStoredSource 옵션을 사용하여 저장된 객체의 funding_rounds.investments 배열 에 있는 필드를 포함하여 객체의 funding_rounds 배열 내에 저장된 모든 필드를 반환합니다. 결과 수를 5 funding_rounds 문서로 제한합니다.

1 db.companies.aggregate(
2   {
3     "$search": {
4       "range": {
5         "path": "funding_rounds.raised_amount",
6         "gte": 5000000,
7         "lte": 10000000
8       },
9       "returnStoredSource": true,
10       "returnScope": {
11         "path": "funding_rounds"
12       }
13     }
14   },
15   {
16     "$limit": 5
17   }
18 )

[
  {
    round_code: 'a',
    raised_amount: 5250000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: {
          name: 'Frazier Technology Ventures',
          permalink: 'frazier-technology-ventures'
        },
        person: null
      },
      {
        financial_org: { name: 'Trinity Ventures', permalink: 'trinity-ventures' },
        person: null
      }
    ]
  },
  {
    round_code: 'b',
    raised_amount: 9500000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: { name: 'Accel Partners', permalink: 'accel-partners' },
        person: null
      },
      {
        financial_org: {
          name: 'Frazier Technology Ventures',
          permalink: 'frazier-technology-ventures'
        },
        person: null
      },
      {
        financial_org: { name: 'Trinity Ventures', permalink: 'trinity-ventures' },
        person: null
      }
    ]
  },
  {
    round_code: 'a',
    raised_amount: 5000000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: {
          name: 'Charles River Ventures',
          permalink: 'charles-river-ventures'
        },
        person: null
      },
      {
        financial_org: {
          name: 'Union Square Ventures',
          permalink: 'union-square-ventures'
        },
        person: null
      },
      {
        financial_org: null,
        person: {
          first_name: 'Marc',
          last_name: 'Andreessen',
          permalink: 'marc-andreessen'
        }
      },
      {
        financial_org: null,
        person: {
          first_name: 'Dick',
          last_name: 'Costolo',
          permalink: 'dick-costolo'
        }
      },
      {
        financial_org: null,
        person: {
          first_name: 'Naval',
          last_name: 'Ravikant',
          permalink: 'naval-ravikant'
        }
      },
      {
        financial_org: null,
        person: {
          first_name: 'Ron',
          last_name: 'Conway',
          permalink: 'ron-conway'
        }
      },
      {
        financial_org: null,
        person: {
          first_name: 'Chris',
          last_name: 'Sacca',
          permalink: 'chris-sacca'
        }
      },
      {
        financial_org: null,
        person: {
          first_name: 'Greg',
          last_name: 'Yaitanes',
          permalink: 'greg-yaitanes'
        }
      },
      {
        financial_org: null,
        person: {
          first_name: 'Brian',
          last_name: 'Pokorny',
          permalink: 'brian-pokorny'
        }
      },
      {
        financial_org: { name: 'SV Angel', permalink: 'sv-angel' },
        person: null
      }
    ]
  },
  {
    round_code: 'e',
    raised_amount: 5166511,
    raised_currency_code: 'USD',
    investments: []
  },
  {
    round_code: 'b',
    raised_amount: 9000000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: {
          name: 'Charles River Ventures',
          permalink: 'charles-river-ventures'
        },
        person: null
      },
      {
        financial_org: { name: 'Redpoint Ventures', permalink: 'redpoint-ventures' },
        person: null
      },
      {
        financial_org: {
          name: 'The Kinsey Hills Group',
          permalink: 'kinsey-hills-group'
        },
        person: null
      }
    ]
  }
]

복합 쿼리

여러 내장된 문서 필드를 쿼리하고 조회합니다.

다음 쿼리는 compound 연산자를 사용하여 동일한 쿼리에서 중첩된 embeddedDocuments 필드의 여러 수준을 검색합니다.

``funding_rounds.raised_currency_code`` 가 USD
funding_rounds.investments.financial_org.name 을(를) Trinity Ventures와(과) 일치시켜야 합니다.

funding_rounds.investments에 있는 필드를 포함하여 funding_rounds 객체 배열 내에 저장된 모든 필드를 반환합니다. 결과 수를 funding_rounds개 문서로 제한합니다.

1 db.companies.aggregate(
2   {
3     "$search": {
4       "compound": {
5         "must": [{
6           "text": {
7             "path": "funding_rounds.raised_currency_code",
8             "query": "usd"
9           }
10         }],
11         "should": [{
12           "phrase": {
13             "path": "funding_rounds.investments.financial_org",
14             "query": "Trinity Ventures",
15           }
16         }]
17       },
18       "returnStoredSource": true,
19       "returnScope": {
20         "path": "funding_rounds"
21       }
22     }
23   },
24   {
25     "$limit": 5
26   }
27 )

[
  {
    round_code: 'a',
    raised_amount: 5250000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: {
          name: 'Frazier Technology Ventures',
          permalink: 'frazier-technology-ventures'
        },
        person: null
      },
      {
        financial_org: { name: 'Trinity Ventures', permalink: 'trinity-ventures' },
        person: null
      }
    ]
  },
  {
    round_code: 'b',
    raised_amount: 9500000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: { name: 'Accel Partners', permalink: 'accel-partners' },
        person: null
      },
      {
        financial_org: {
          name: 'Frazier Technology Ventures',
          permalink: 'frazier-technology-ventures'
        },
        person: null
      },
      {
        financial_org: { name: 'Trinity Ventures', permalink: 'trinity-ventures' },
        person: null
      }
    ]
  },
  {
    round_code: 'c',
    raised_amount: 25000000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: { name: 'DAG Ventures', permalink: 'dag-ventures' },
        person: null
      },
      {
        financial_org: { name: 'Accel Partners', permalink: 'accel-partners' },
        person: null
      },
      {
        financial_org: { name: 'Trinity Ventures', permalink: 'trinity-ventures' },
        person: null
      },
      {
        financial_org: {
          name: 'Frazier Technology Ventures',
          permalink: 'frazier-technology-ventures'
        },
        person: null
      }
    ]
  },
  {
    round_code: 'angel',
    raised_amount: 500000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: null,
        person: {
          first_name: 'Peter',
          last_name: 'Thiel',
          permalink: 'peter-thiel'
        }
      },
      {
        financial_org: null,
        person: {
          first_name: 'Reid',
          last_name: 'Hoffman',
          permalink: 'reid-hoffman'
        }
      }
    ]
  },
  {
    round_code: 'a',
    raised_amount: 12700000,
    raised_currency_code: 'USD',
    investments: [
      {
        financial_org: { name: 'Accel Partners', permalink: 'accel-partners' },
        person: null
      },
      {
        financial_org: null,
        person: {
          first_name: 'Mark',
          last_name: 'Pincus',
          permalink: 'mark-pincus'
        }
      },
      {
        financial_org: null,
        person: {
          first_name: 'Reid',
          last_name: 'Hoffman',
          permalink: 'reid-hoffman'
        }
      }
    ]
  }
]

Group Children by Parent

Group children by parent using the searchRootDocumentId meta field.

The following query uses the range (MongoDB Search Operator) to query the funding_rounds.raised_amount field for amount greater than and equal to 5000000 and less than and equal to 10000000. It sets the query scope as funding_rounds field using the returnScope option. It groups the matching funding_rounds under each parent company by using the searchRootDocumentId meta field as the group key and computes the average raised_amount per company in the avgRaisedAmount field. It sorts the results by avgRaisedAmount in descending order and limits the number of results to 10 companies.

1 db.companies.aggregate([
2   {
3     "$search": {
4       "returnStoredSource": true,
5       "returnScope": {
6         "path": "funding_rounds"
7       },
8       "range": {
9         "path": "funding_rounds.raised_amount",
10         "gte": 5000000,
11         "lte": 10000000
12       }
13     }
14   },
15   {
16     "$group": {
17       "_id": { "$meta": "searchRootDocumentId" },
18       "funding_rounds": {
19         "$push": {
20           "round_code": "$round_code",
21           "raised_amount": "$raised_amount",
22           "raised_currency_code": "$raised_currency_code"
23         }
24       },
25       "avgRaisedAmount": { "$avg": "$raised_amount" }
26     }
27   },
28   { "$sort": { "avgRaisedAmount": -1 } },
29   { "$limit": 10 }
30 ])

[
  {
    _id: ObjectId('52cdef7d4bab8bd675298f82'),
    funding_rounds: [
      {
        round_code: 'a',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7e4bab8bd67529af80'),
    funding_rounds: [
      {
        round_code: 'b',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7f4bab8bd67529be3d'),
    funding_rounds: [
      {
        round_code: 'a',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7f4bab8bd67529c52d'),
    funding_rounds: [
      {
        round_code: 'unattributed',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7e4bab8bd67529ab31'),
    funding_rounds: [
      {
        round_code: 'c',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      },
      {
        round_code: 'a',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7e4bab8bd67529aa94'),
    funding_rounds: [
      {
        round_code: 'b',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7f4bab8bd67529be6f'),
    funding_rounds: [
      {
        round_code: 'a',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7c4bab8bd6752985cb'),
    funding_rounds: [
      {
        round_code: 'd',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7d4bab8bd675299fd1'),
    funding_rounds: [
      {
        round_code: 'c',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  },
  {
    _id: ObjectId('52cdef7f4bab8bd67529c2c8'),
    funding_rounds: [
      {
        round_code: 'debt_round',
        raised_amount: 10000000,
        raised_currency_code: 'USD'
      }
    ],
    avgRaisedAmount: 10000000
  }
]

Fetch Parent Fields After Filtering

Retrieve the fields from the parent document after filtering on the embedded document fields.

The following query uses the range (MongoDB Search Operator) to query the funding_rounds.raised_amount field for amount greater than and equal to 5000000 and less than and equal to 10000000. It sets the query scope as funding_rounds field using the returnScope option. It sorts the matching funding_rounds by raised_amount in descending order and limits the results to the top 10 funding rounds. It then uses the searchRootDocumentId meta field to join each funding round back to its parent company in the companies collection and returns the company's name alongside the funding round's round_code, raised_amount, and raised_currency_code fields.

1 db.companies.aggregate([
2   {
3     "$search": {
4       "returnStoredSource": true,
5       "returnScope": {
6         "path": "funding_rounds"
7       },
8       "range": {
9         "path": "funding_rounds.raised_amount",
10         "gte": 5000000,
11         "lte": 10000000
12       }
13     }
14   },
15   { "$sort": { "raised_amount": -1 } },
16   { "$limit": 10 },
17   { "$addFields": { "root_id": { "$meta": "searchRootDocumentId" } } },
18   {
19     "$lookup": {
20       "from": "companies",
21       "localField": "root_id",
22       "foreignField": "_id",
23       "as": "company"
24     }
25   },
26   { "$unwind": "$company" },
27   {
28     "$project": {
29       "_id": 0,
30       "round_code": 1,
31       "raised_amount": 1,
32       "raised_currency_code": 1,
33       "company.name": 1
34     }
35   }
36 ])

[
  {
    round_code: 'partial',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'WeFi' }
  },
  {
    round_code: 'b',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'LinkedIn' }
  },
  {
    round_code: 'a',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'Lotame' }
  },
  {
    round_code: 'c',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'OpenX' }
  },
  {
    round_code: 'b',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'AddThis' }
  },
  {
    round_code: 'a',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'Terabitz' }
  },
  {
    round_code: 'b',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'Six Apart' }
  },
  {
    round_code: 'a',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'Snocap' }
  },
  {
    round_code: 'b',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'Wikia' }
  },
  {
    round_code: 'unattributed',
    raised_amount: 10000000,
    raised_currency_code: 'USD',
    company: { name: 'Mashery' }
  }
]

돌아가기

searchSequenceToken

성능 옵션

1	{
2	"mappings": {
3	"dynamic": false,
4	"fields": {
5	"funding_rounds": {
6	"type": "embeddedDocuments",
7	"dynamic": true,
8	"fields": {
9	"investments": {
10	"type": "embeddedDocuments",
11	"dynamic": true
12	}
13	},
14	"storedSource": {
15	"include": [
16	"round_code",
17	"raised_currency_code",
18	"raised_amount",
19	"investments.person",
20	"investments.financial_org"
21	]
22	}
23	}
24	}
25	}
26	}

1	db.companies.aggregate(
2	{
3	"$search": {
4	"range": {
5	"path": "funding_rounds.raised_amount",
6	"gte": 5000000,
7	"lte": 10000000
8	},
9	"returnStoredSource": true,
10	"returnScope": {
11	"path": "funding_rounds"
12	}
13	}
14	},
15	{
16	"$limit": 5
17	}
18	)

1	db.companies.aggregate(
2	{
3	"$search": {
4	"compound": {
5	"must": [{
6	"text": {
7	"path": "funding_rounds.raised_currency_code",
8	"query": "usd"
9	}
10	}],
11	"should": [{
12	"phrase": {
13	"path": "funding_rounds.investments.financial_org",
14	"query": "Trinity Ventures",
15	}
16	}]
17	},
18	"returnStoredSource": true,
19	"returnScope": {
20	"path": "funding_rounds"
21	}
22	}
23	},
24	{
25	"$limit": 5
26	}
27	)

1	db.companies.aggregate([
2	{
3	"$search": {
4	"returnStoredSource": true,
5	"returnScope": {
6	"path": "funding_rounds"
7	},
8	"range": {
9	"path": "funding_rounds.raised_amount",
10	"gte": 5000000,
11	"lte": 10000000
12	}
13	}
14	},
15	{
16	"$group": {
17	"_id": { "$meta": "searchRootDocumentId" },
18	"funding_rounds": {
19	"$push": {
20	"round_code": "$round_code",
21	"raised_amount": "$raised_amount",
22	"raised_currency_code": "$raised_currency_code"
23	}
24	},
25	"avgRaisedAmount": { "$avg": "$raised_amount" }
26	}
27	},
28	{ "$sort": { "avgRaisedAmount": -1 } },
29	{ "$limit": 10 }
30	])