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Use o Atlas Search com um Sistema Atlas

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  • Concluir os pré-requisitos
  • Revise as limitações
  • Criar um Atlas Search Index e Executar uma query
  • Use o Atlas Vector Search com um sistema Atlas
  • Ações suportadas

Este tutorial mostra como utilizar o comando atlas deployments para criar um índice de pesquisa, executar uma query e trabalhar com a pesquisa vetorial.

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 Docker.

    Observação

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

    Podman v5.0+ também é suportado para 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 usar o Atlas CLI com o Atlas Vector Search, você deve criar um sistema do Atlas com o MongoDB 7.0.5 ou posterior. Se você criou uma implantação local no 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 deverá criar uma nova implantação 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 Atlas Search Index e Executar uma query

Utilize o comando atlas deployments para trabalhar com Atlas Search. Para saber mais, consulte Atlas Search.

Você pode executar este comando das seguintes maneiras:

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

    Observação

    O Modo Interativo permite a você criar um índice de pesquisa básico do Atlas 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 Atlas Search .

  1. Execute o seguinte comando:

    atlas deployments search indexes create

  2. Especifique o sistema e pressione Enter..

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

  4. Especifique o reconhecimento de data center sample_mflix e pressione Enter..

  5. Especifique a collection 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 a implantação a qual vai se conectar e pressione Enter.

  3. Especifique mongosh e pressione Enter..

3

Mudar 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 Atlas Search .

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 a implantação a qual vai se conectar e pressione Enter.

  3. Especifique mongosh e pressione Enter..

3

Mudar 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 Atlas Search .

  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 a implantação a qual vai se conectar e pressione Enter.

  3. Especifique mongosh e pressione Enter..

4

Mudar 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 Atlas Vector Search com um sistema Atlas

Utilize o comando atlas deployments para trabalhar com o Atlas Vector Search. Para saber mais, consulte Como Indexar Incorporações de Vetores para Vector Search.

Importante

Para usar o Atlas CLI com o Atlas Vector Search, você deve criar um sistema do Atlas com o MongoDB 7.0.5 ou posterior. Se você criou uma implantação local no 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 deverá criar uma nova implantação 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 Atlas Search .

  1. Execute o seguinte comando:

    atlas deployments search indexes create --file indexDef-vector.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 a implantação a qual vai se conectar e pressione Enter.

  3. Especifique mongosh e pressione Enter..

4

Mudar para o banco de dados sample_mflix.

use sample_mflix
5

Execute uma query de exemplo.

Importante

Copiar e colar um campo queryVector com muitos números no seu terminal pode demorar um pouco dependendo da sua máquina.

db.embedded_movies.aggregate([
  {
    "$vectorSearch": {
      "index": "vectorSearchIndex",
      "path": "plot_embedding",
      "queryVector": 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    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',
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    title: 'Black Moon',
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    title: 'Forest Warrior',
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    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
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    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',
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  },
  {
    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
  }
]

Ações suportadas

Para saber todas as ações compatíveis com atlas deployments, consulte implantações do Atlas.

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Implante com Docker

Próximo

Automações de teste