Você pode usar a opção returnScope para definir o contexto da query e retornar arrays de objetos como documentos individuais.
Requisitos
Para recuperar objetos aninhados como documentos individuais usando returnScope, você deve:
Índice as arrays de objetos como o tipo embeddedDocuments.
Defina storedSource para os campos aninhados que você deseja recuperar. A pesquisa do MongoDB retorna apenas os campos definidos no
storedSource.Defina a opção returnStoredSource como
truena query.
Sintaxe
returnScope tem a seguinte sintaxe em suas queries:
Para saber mais sobre sintaxe de query, consulte $search.
Comportamento
A opção returnScope define o contexto de recuperação para a query. Se você especificar returnScope em sua query, o MongoDB Search pontua, classifica e conta cada documento incorporado como se fosse um documento individual.
Considerações
Quando você usa a opção returnScope, o MongoDB pesquisa retorna apenas os campos que você configurou como storedSource dentro do embeddedDocument. Os campos fora do caminho embeddedDocument (como os campos no nível da raiz) e os campos que não estão configurados como storedSource não são retornados.
Na especificação do operador, você deve especificar o caminho completo para o campo que deseja fazer a query. Ao usar a opção returnScope, você deve garantir que todos os caminhos de especificações do operador estejam aninhados em returnScope.path. Para fazer query em um campo fora do returnScope.path, você deve usar o operador hasAncestor ou hasRoot. Para aprender mais, consulte:
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.
Exemplos
Os exemplos a seguir demonstram como usar a opção returnScope em consultas. Os exemplos usam o conjunto de dados de amostra sample_training.companies. Se você carregar os dados no seu cluster e criar o índice de amostra nos campos da coleção, poderá tentar as seguintes consultas nos dados de amostra.
Índice de amostra
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 }
A definição de índice anterior configura a pesquisa do MongoDB para:
Indexe os campos
funding_roundsefunding_rounds.investmentscomo o tipoembeddedDocuments.Indexe todos os campos indexáveis dinamicamente aninhados no array de objetos
funding_roundsefunding_rounds.investments.Armazene os seguintes campos em
mongot:funding_rounds.round_codefunding_rounds.raised_currency_codefunding_rounds.raised_amountfunding_rounds.investments.personfunding_rounds.investments.financial_org
Você pode usar o embeddedDocument Operador para realizar queries elemento a elemento em ambos os campos funding_rounds e funding_rounds.investments. As seções a seguir demonstram algumas queries de amostra que usam a opção returnScope para recuperar os campos embeddedDocuments como documentos individuais.
{ ..., "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>" } }, ... ] }, ... ], ... }
Exemplos de queries
As seções seguintes demonstram queries de exemplo que usam a opção returnScope para recuperar campos em campos do tipo embeddedDocuments que foram armazenados em mongot.
A query a seguir usa o range (Operador de Pesquisa do MongoDB) para consultar o campo funding_rounds.raised_amount para uma quantidade maior e igual a 5000000 e menor e igual a 10000000. Define o escopo da consulta como funding_rounds campo usando a opção returnScope. Retorna todos os campos armazenados dentro da array de objetos funding_rounds, incluindo campos na array de objetos funding_rounds.investments que foram armazenados usando a opção returnStoredSource. Limita o número de resultados a apenas 5 funding_rounds documentos.
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 } ] } ]
A query a seguir usa o compound operador para pesquisar vários níveis de campos embeddedDocuments aninhados na mesma query:
Deve corresponder a "funding_rounds.raised_currency_code" com
USDDeve corresponder
funding_rounds.investments.financial_org.nameaTrinity Ventures
Ele retorna todos os campo armazenar dentro do array de objeto funding_rounds, incluindo os campo no funding_rounds.investments. Limita o número de resultados a apenas 5 funding_rounds documentos.
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' } } ] } ]
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 } ]
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' } } ]