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Use o MongoDB Search e a pesquisa vetorial com o Atlas

Este tutorial mostra como usar o comando atlas deployments para criar um índice do MongoDB Search, executar uma query e trabalhar com o MongoDB Vector Search.

Concluir os pré-requisitos

Antes de começar, cumpra os seguintes pré-requisitos:

Importante

Para obter informações de compatibilidade sobre cada produto na lista de dependências, consulte a documentação de instalação do produto.

  • Instale o Atlas CLI.

    Exemplo (MacOS):

    brew install mongodb-atlas-cli

    Para saber mais sobre as instruções de instalação da Atlas CLI para outros sistemas operacionais, consulte Instalar ou Atualizar a Atlas CLI.

  • Instale o mongosh versão 2.0 ou posterior.

    Exemplo (MacOS):

    brew install mongosh

    Para saber mais sobre as instruções de instalação do mongosh para outros sistemas operacionais, consulte Instalar o mongosh.

  • (Opcional) Instale o Compass versão 1.39.4 ou posterior.

    Exemplo (MacOS):

    brew install mongodb-compass

    Para saber mais sobre as instruções de instalação do Compass para outros sistemas operacionais, consulte Baixar e instalar o Compass.

  • Instale as ferramentas do banco de dados MongoDB.

    Exemplo (MacOS):

    brew tap mongodb/brew && brew install mongodb-database-tools

    Para saber mais sobre as instruções de instalação das ferramentas de MongoDB database para outros sistemas operacionais, consulte Instalando as Database Tools de dados.

  • Instale o docker.

    Observação

    O Docker requer uma conexão de rede para extrair e armazenar em cache imagens do MongoDB .

    O Podman v5.0+ também é compatível com versões do Linux RHEL.

  • Criar uma implementação do Atlas.

    Exemplo:

    atlas deployments setup

    Para saber mais, consulte Criar um Sistema do Atlas Local.

    Importante

    Para utilizar o Atlas CLI com MongoDB Vector Search, você deve criar uma implantação do Atlas com MongoDB 7.0.5 ou posterior. Se você criou uma implantação local do Atlas com uma versão anterior do MongoDB , não obterá a versão mais recente do MongoDB automaticamente. Você deve excluir as imagens e implantações anteriores. Em seguida, você deve criar uma nova implantação do Atlas .

  • Baixe e carregue os dados de amostra.

    Exemplo:

    1. Execute o seguinte comando para baixar os dados de amostra:

      curl  https://atlas-education.s3.amazonaws.com/sampledata.archive -o sampledata.archive

    2. Copie e cole o seguinte comando no seu terminal e substitua {port-number} pela porta para sua implantação:

      mongorestore --archive=sampledata.archive --port={port-number}

Revise as limitações

Aplicam-se as seguintes limitações:

  • Você não pode realizar pesquisas simultâneas .

  • Você não pode exceder 1024 cláusulas booleanas.

Criar um índice de pesquisa MongoDB e executar uma query

Utilize o comando atlas deployments para trabalhar com a Pesquisa MongoDB . Para aprender mais, consulte MongoDB Search.

Você pode executar este comando das seguintes maneiras:

  • Modo Interativo: o comando solicita as configurações do MongoDB Search.

    Observação

    O modo interativo permite criar um índice básico do MongoDB Search com configurações padrão.

  • Modo não interativo (sinalizadores): você executa o comando com as opções especificadas. O comando não solicita que você forneça valores adicionais.

  • Modo Não Interativo (Arquivo de Configuração): você executa o comando com as configurações especificadas no arquivo de configuração. O comando não solicita que você forneça valores adicionais.

Clique em uma das abas a seguir para verificar o comando de seu modo preferido.

1

Crie um índice de pesquisa MongoDB .

  1. Execute o seguinte comando:

    atlas deployments search indexes create

  2. Especifique a implantação e pressione Enter.

  3. Especifique searchIndex como o nome do índice e pressione Enter.

  4. Especifique o banco de banco de dados sample_mflix e pressione Enter.

  5. Especifique a coleção movies e pressione Enter.

2

Conecte-se à implantação.

  1. Execute o seguinte comando para se conectar a uma implantação:

    atlas deployments connect

  2. Especifique o sistema à qual se conectar e pressione Enter.

  3. Especifique mongosh e pressione Enter.

3

Alternar para o banco de dados sample_mflix.

use sample_mflix
4

Execute uma query de exemplo.

db.movies.aggregate([
  {
    $search: {
      "index": "searchIndex",
      "text": {
        "query": "baseball",
        "path": "plot"
      }
    }
  },
  {
    $limit: 5
  },
  {
    $project: {
      "_id": 0,
      "title": 1,
      "plot": 1
    }
  }
])
[
  {
    plot: 'A trio of guys try and make up for missed opportunities in childhood by forming a three-player baseball team to compete against standard children baseball squads.',
    title: 'The Benchwarmers'
  },
  {
    plot: 'A young boy is bequeathed the ownership of a professional baseball team.',
    title: 'Little Big League'
  },
  {
    plot: 'A trained chimpanzee plays third base for a minor-league baseball team.',
    title: 'Ed'
  },
  {
    plot: 'The story of the life and career of the famed baseball player, Lou Gehrig.',
    title: 'The Pride of the Yankees'
  },
  {
    plot: 'Babe Ruth becomes a baseball legend but is unheroic to those who know him.',
    title: 'The Babe'
  }
]
1

Crie um índice de pesquisa MongoDB .

Copie e cole o seguinte comando no seu terminal e substitua {myRs} pelo seu sistema:

atlas deployments search indexes create searchIndex --deploymentName {myRs} --db sample_mflix --collection movies
2

Conecte-se à implantação.

  1. Execute o seguinte comando para se conectar a uma implantação:

    atlas deployments connect

  2. Especifique o sistema à qual se conectar e pressione Enter.

  3. Especifique mongosh e pressione Enter.

3

Alternar para o banco de dados sample_mflix.

use sample_mflix
4

Execute uma query de exemplo.

db.movies.aggregate([
  {
    $search: {
      "index": "searchIndex",
      "text": {
        "query": "baseball",
        "path": "plot"
      }
    }
  },
  {
    $limit: 5
  },
  {
    $project: {
      "_id": 0,
      "title": 1,
      "plot": 1
    }
  }
])
[
  {
    plot: 'A trio of guys try and make up for missed opportunities in childhood by forming a three-player baseball team to compete against standard children baseball squads.',
    title: 'The Benchwarmers'
  },
  {
    plot: 'A young boy is bequeathed the ownership of a professional baseball team.',
    title: 'Little Big League'
  },
  {
    plot: 'A trained chimpanzee plays third base for a minor-league baseball team.',
    title: 'Ed'
  },
  {
    plot: 'The story of the life and career of the famed baseball player, Lou Gehrig.',
    title: 'The Pride of the Yankees'
  },
  {
    plot: 'Babe Ruth becomes a baseball legend but is unheroic to those who know him.',
    title: 'The Babe'
  }
]
1

Crie um arquivo de configuração indexDef.json.

{
  "collectionName": "movies",
  "database": "sample_mflix",
  "mappings": {
    "dynamic": true
  },
  "name": "searchIndex"
}
2

Crie um índice de pesquisa MongoDB .

  1. Execute o seguinte comando:

    atlas deployments search indexes create --file indexDef.json

  2. Especifique o sistema e pressione Enter.

3

Conecte-se à implantação.

  1. Execute o seguinte comando para se conectar a uma implantação:

    atlas deployments connect

  2. Especifique o sistema à qual se conectar e pressione Enter.

  3. Especifique mongosh e pressione Enter.

4

Alternar para o banco de dados sample_mflix.

use sample_mflix
5

Execute uma query de exemplo.

db.movies.aggregate([
  {
    $search: {
      "index": "searchIndex",
      "text": {
        "query": "baseball",
        "path": "plot"
      }
    }
  },
  {
    $limit: 5
  },
  {
    $project: {
      "_id": 0,
      "title": 1,
      "plot": 1
    }
  }
])
[
  {
    plot: 'A trio of guys try and make up for missed opportunities in childhood by forming a three-player baseball team to compete against standard children baseball squads.',
    title: 'The Benchwarmers'
  },
  {
    plot: 'A young boy is bequeathed the ownership of a professional baseball team.',
    title: 'Little Big League'
  },
  {
    plot: 'A trained chimpanzee plays third base for a minor-league baseball team.',
    title: 'Ed'
  },
  {
    plot: 'The story of the life and career of the famed baseball player, Lou Gehrig.',
    title: 'The Pride of the Yankees'
  },
  {
    plot: 'Babe Ruth becomes a baseball legend but is unheroic to those who know him.',
    title: 'The Babe'
  }
]

Use o MongoDB Vector Search com uma implantação do Atlas

Use o comando atlas deployments para trabalhar com a pesquisa vetorial do MongoDB. Para aprender mais, consulte Como Indexar Embeddings para pesquisa vetorial.

Importante

Para utilizar o Atlas CLI com MongoDB Vector Search, você deve criar uma implantação do Atlas com MongoDB 7.0.5 ou posterior. Se você criou uma implantação local do Atlas com uma versão anterior do MongoDB , não obterá a versão mais recente do MongoDB automaticamente. Você deve excluir as imagens e implantações anteriores. Em seguida, você deve criar uma nova implantação do Atlas .

1

Crie um arquivo de configuração indexDef-vector.json.

{
  "name": "vectorSearchIndex",
  "type": "vectorSearch",
  "collectionName": "embedded_movies",
  "database": "sample_mflix",
  "fields": [
    {
      "type": "vector",
      "path": "plot_embedding",
      "numDimensions": 1536,
      "similarity": "euclidean"
    }
  ]
}
2

Crie um índice de pesquisa MongoDB .

  1. Execute o seguinte comando:

    atlas deployments search indexes create --file indexDef-vector.json

    Você deve especificar o caminho para o arquivo se o indexDef-vector.json não estiver no diretório de onde você deseja executar o comando.

  2. Especifique o sistema e pressione Enter.

3

Crie o arquivo query-embeddings.js.

  1. Crie um arquivo denominado query-embeddings.js para armazenar as incorporações de query.

  2. Copie e cole as seguintes incorporações para a string fantasy adventure no arquivo query-embeddings.js.

    QUERY_EMBEDDING = 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  1. Salve o arquivo query-embeddings.js.

4

Conecte-se à implantação.

  1. Execute o seguinte comando para se conectar a uma implantação:

    atlas deployments connect

  2. Especifique o sistema à qual se conectar e pressione Enter.

  3. Especifique mongosh e pressione Enter.

5

Alternar para o banco de dados sample_mflix.

use sample_mflix
6

Carregue o arquivo query-embeddings.js.

Para carregar o arquivo, execute o seguinte comando, substituindo <path-to-file> pelo caminho completo para seu arquivo query-embeddings.js.

load('<path-to-file>/query-embeddings.js')

Você pode verificar se o arquivo foi carregado corretamente executando o seguinte comando:

QUERY_EMBEDDING.length
1536
7

Execute uma query de exemplo.

db.embedded_movies.aggregate([
  {
    "$vectorSearch": {
      "index": "vectorSearchIndex",
      "path": "plot_embedding",
      "queryVector": QUERY_EMBEDDING,
      "numCandidates": 150,
      "limit": 10
    }
  },
  {
    "$project": {
      "_id": 0,
      "plot": 1,
      "title": 1,
      "score": { $meta: "vectorSearchScore" }
    }
  }
])
[
  {
    plot: 'When two girls move to the country to be near their ailing mother, they have adventures with the wonderous forest spirits who live nearby.',
    title: 'My Neighbor Totoro',
    score: 0.9999986886978149
  },
  {
    plot: "To escape a war, a girl flees to a remote farmhouse and becomes part of an expansive family's unusual, perhaps even supernatural lifestyle.",
    title: 'Black Moon',
    score: 0.8282386660575867
  },
  {
    plot: 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.',
    title: 'Forest Warrior',
    score: 0.8196926712989807
  },
  {
    plot: 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.',
    title: 'Forest Warrior',
    score: 0.8196901082992554
  },
  {
    plot: 'An adventurous girl finds another world that is a strangely idealized version of her frustrating home, but it has sinister secrets.',
    title: 'Coraline',
    score: 0.815956711769104
  },
  {
    plot: "Set in a medieval village that is haunted by a werewolf, a young girl falls for an orphaned woodcutter, much to her family's displeasure.",
    title: 'Red Riding Hood',
    score: 0.8112794160842896
  },
  {
    plot: 'Their women having been enslaved by the local pack of lesbian vampires thanks to an ancient curse, the remaining menfolk of a rural town send two hapless young lads out onto the moors as a sacrifice.',
    title: 'Vampire Killers',
    score: 0.8102427124977112
  },
  {
    plot: 'In a mythical land, a man and a young boy investigate a series of unusual occurrences.',
    title: 'Tales from Earthsea',
    score: 0.8100577592849731
  },
  {
    plot: 'Because of the actions of her irresponsible parents, a young girl is left alone on a decrepit country estate and survives inside her fantastic imagination.',
    title: 'Tideland',
    score: 0.8080059885978699
  },
  {
    plot: 'Two siblings discover a supernatural escape from a troubled home, but find their bond tested when reality threatens to tear their family apart.',
    title: 'One and Two',
    score: 0.8072565197944641
  }
]

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Para aprender todas as ações compatíveis com atlas deployments, consulte atlas-deployments.

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