{"id":2334,"date":"2016-07-14T15:00:00","date_gmt":"2016-07-14T15:00:00","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=2334"},"modified":"2025-06-13T20:59:40","modified_gmt":"2025-06-14T03:59:40","slug":"using-full-text-search-fts-in-couchbase-with-the-nodejs-sdk","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/pt\/using-full-text-search-fts-in-couchbase-with-the-nodejs-sdk\/","title":{"rendered":"Usando a pesquisa de texto completo (FTS) no Couchbase com o SDK do Node.js"},"content":{"rendered":"

Quando desenvolvo aplicativos, sempre me deparo com um cen\u00e1rio em que preciso pesquisar um conjunto espec\u00edfico de texto em um bloco de dados. Eu, como muitos outros, muitas vezes me vejo optando pelo caminho mais f\u00e1cil e fazendo uma consulta com curinga. No entanto, o uso de curingas em uma consulta pode causar um significativo desperd\u00edcio de desempenho e inefici\u00eancias em seu aplicativo ou banco de dados. \u00c9 nesse ponto que a pesquisa de texto completo (FTS) entra em a\u00e7\u00e3o.<\/p>\n

A pesquisa de texto completo opera em \u00edndices de texto completo e \u00e9 muito mais eficiente do que trabalhar com curingas quando se trata de pesquisar palavras e frases em um banco de dados. At\u00e9 agora, para que isso fosse poss\u00edvel, era necess\u00e1rio usar outro software de pesquisa, como o Solr ou o ElasticSearch. A partir do Couchbase 4.5, o FTS est\u00e1 dispon\u00edvel como visualiza\u00e7\u00e3o do desenvolvedor para traz\u00ea-lo para uma \u00fanica plataforma.<\/p>\n

Vamos dar uma olhada em como usar a pesquisa de texto completo em um aplicativo Node.js usando o SDK do Node.js para o Couchbase Server. O que vem a seguir pressup\u00f5e que voc\u00ea j\u00e1 tenha o Node.js instalado e pronto para o desenvolvimento. Tamb\u00e9m pressup\u00f5e que voc\u00ea esteja usando o Couchbase Server 4.5 ou superior.<\/p>\n

Para manter as coisas simples, vamos trabalhar em um novo projeto Node.js com uma hist\u00f3ria simples. Vamos come\u00e7ar criando um novo projeto em algum lugar em nossa m\u00e1quina. Vou chamar esse projeto de curr\u00edculo<\/strong>. Como voc\u00ea deve ter adivinhado pelo nome do projeto, vamos criar um aplicativo do tipo parsing para curr\u00edculos de candidatos a emprego. Podemos usar o FTS para procurar palavras-chave ou frases que sejam relevantes para determinados cargos. Como o FTS oferece pontua\u00e7\u00e3o de pesquisa, podemos ver quais candidatos podem ser mais qualificados para o cargo.<\/p>\n

Cria\u00e7\u00e3o de um novo projeto Node.js<\/h2>\n

Usando um Terminal (Mac e Linux) ou um Prompt de Comando (Windows), execute o seguinte com o projeto como o diret\u00f3rio ativo atual:<\/p>\n

\r\nnpm init -y\r\n<\/code><\/pre>\n
O comando acima inicializar\u00e1 um novo projeto Node.js. A partir de agora, todas as atividades do Terminal e do prompt de comando ser\u00e3o realizadas com o projeto como o diret\u00f3rio de trabalho atual.<\/p>\n
Vamos criar mais um script Node.js do que um aplicativo RESTful. Dito isso, h\u00e1 apenas um requisito de depend\u00eancia, que \u00e9 o Couchbase Node.js SDK. Para instal\u00e1-lo, execute o seguinte no prompt de comando ou no terminal:<\/p>\n
\r\nnpm install couchbase --save\r\n<\/code><\/pre>\n
Embora ainda n\u00e3o vamos come\u00e7ar a programar, queremos criar nosso arquivo Node.js principal. Criar app.js<\/strong> na raiz de seu projeto.<\/p>\n
Cria\u00e7\u00e3o de um \u00edndice de pesquisa de texto completo<\/h2>\n
Antes de come\u00e7ar a usar a pesquisa de texto completo, voc\u00ea deve criar um \u00edndice especial. Isso pode ser feito na se\u00e7\u00e3o \u00cdndices -> Texto completo<\/strong> do painel de controle administrativo do Couchbase.<\/p>\n
<\/p>\n
Nessa se\u00e7\u00e3o, voc\u00ea deve escolher Novo \u00edndice de texto completo<\/strong> e escolha o nome e o bucket para aplic\u00e1-lo. Para este exemplo, usaremos o padr\u00e3o<\/strong> e um \u00edndice de Busca de curr\u00edculo<\/strong>. Nosso \u00edndice ser\u00e1 bem b\u00e1sico, portanto, recomendo que voc\u00ea d\u00ea uma olhada no documenta\u00e7\u00e3o<\/a> para que voc\u00ea possa atender melhor \u00e0s suas necessidades.<\/p>\n
Depois que o \u00edndice tiver sido criado, clique no bot\u00e3o atualizar. Neste ponto, voc\u00ea pode test\u00e1-lo por meio do painel ou de seu pr\u00f3prio c\u00f3digo.<\/p>\n
Desenvolvimento do aplicativo Node.js<\/h2>\n
Apenas para reiterar, este projeto ser\u00e1 bastante simples. Voc\u00ea certamente pode expandir essa ideia e criar um aplicativo completo de avalia\u00e7\u00e3o de curr\u00edculo. Para n\u00f3s, estamos apenas arranhando a superf\u00edcie das possibilidades.<\/p>\n
Abra o arquivo app.js<\/strong> e inclua o seguinte c\u00f3digo JavaScript:<\/p>\n
\r\nvar Couchbase = require(\"couchbase\");\r\n\r\nvar cluster = new Couchbase.Cluster(\"couchbase:\/\/localhost\")\r\nvar bucket = cluster.openBucket(\"default\");\r\n<\/code><\/pre>\n
No exemplo acima, estamos importando a depend\u00eancia que baixamos e estabelecendo uma conex\u00e3o com o cluster do Couchbase de nossa escolha. Neste caso, \u00e9 um cluster de n\u00f3 \u00fanico em minha m\u00e1quina local.<\/p>\n
Antes de come\u00e7armos a realizar opera\u00e7\u00f5es de pesquisa de texto completo, vamos pensar em nosso modelo de dados. Digamos que cada curr\u00edculo seja um documento no banco de dados. Por exemplo, aqui est\u00e1 meu curr\u00edculo:<\/p>\n
\r\n{\r\n    \"firstname\": \"Nic\",\r\n    \"lastname\": \"Raboy\",\r\n    \"skills\": [\r\n        \"java\",\r\n        \"node.js\",\r\n        \"golang\",\r\n        \"nosql\"\r\n    ],\r\n    \"summary\": \"\",\r\n    \"social\": {\r\n        \"github\": \"https:\/\/www.github.com\/nraboy\",\r\n        \"twitter\": \"https:\/\/www.twitter.com\/nraboy\"\r\n    },\r\n    \"employment\": [\r\n        {\r\n            \"employer\": \"Couchbase\",\r\n            \"title\": \"Developer Advocate\",\r\n            \"location\": \"San Francisco\"\r\n        }\r\n    ]\r\n}\r\n<\/code><\/pre>\n
Sim, \u00e9 claro que este n\u00e3o \u00e9 meu curr\u00edculo real. \u00c9 apenas um exemplo para ver com o que vamos trabalhar. Agora, digamos que queremos encontrar todos os curr\u00edculos em que a pessoa tenha experi\u00eancia anterior como defensor de desenvolvedores. No Node.js, podemos criar o seguinte:<\/p>\n
\r\nvar SearchQuery = Couchbase.SearchQuery;\r\nvar query = SearchQuery.new(\"resume-search\", SearchQuery.match(\"developer advocate\"));\r\nbucket.query(query, function(error, result, meta) {\r\n    if(error) {\r\n        return console.log(\"ERROR: \", error);\r\n    }\r\n    for (var i = 0; i < result.length; i++) {\r\n        console.log({\"id\": result[i].id, \"score\": result[i].score});\r\n    }\r\n    return;\r\n});\r\n<\/code><\/pre>\n
Como eu indiquei que era Developer Advocate no meu hist\u00f3rico de emprego, meu registro aparecer\u00e1. No entanto, a consulta do FTS acima \u00e9 bastante vaga. Se houver \"developer advocate\" em qualquer propriedade do documento, saberemos sobre ele. Talvez queiramos restringir a consulta especificamente ao hist\u00f3rico de empregos. Nesse caso, podemos alterar nosso Pesquisa<\/code> para o seguinte:<\/p>\n
\r\nvar query = SearchQuery.new(\"resume-search\", SearchQuery.match(\"developer advocate\").field(\"employment.title\"));\r\n<\/code><\/pre>\n
Observe o uso da palavra campo<\/code> fun\u00e7\u00e3o? Voc\u00ea tamb\u00e9m pode usar campos<\/code> e passar uma matriz de campos para pesquisa.<\/p>\n
H\u00e1 muitas outras maneiras de pesquisar dados usando o FTS e o SDK do Node.js. Para obter algumas informa\u00e7\u00f5es sobre o uso do FTS, consulte a se\u00e7\u00e3o documenta\u00e7\u00e3o do desenvolvedor<\/a> ou o Documenta\u00e7\u00e3o da API do Node.js<\/a>.<\/p>\n
Conclus\u00e3o<\/h2>\n
Se voc\u00ea precisar consultar dados curinga de maneira eficiente, o Couchbase e o SDK do Node.js o ajudar\u00e3o com seu suporte \u00e0 pesquisa de texto completo (FTS). H\u00e1 cen\u00e1rios muito mais complexos para a pesquisa de texto completo do que os que mencionei. Por exemplo, talvez voc\u00ea queira come\u00e7ar a adicionar condi\u00e7\u00f5es \u00e0 pesquisa ou visualizar informa\u00e7\u00f5es de faceta. Tudo isso pode ser lido na se\u00e7\u00e3o Portal do desenvolvedor do Couchbase<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"
When I develop applications I always find myself running into a scenario where I need to search for a particular set of text within a chunk of data. I, like many others, often find myself taking the easy way out […]<\/p>","protected":false},"author":63,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1816,2165,1822,1812],"tags":[1505],"ppma_author":[9032],"class_list":["post-2334","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-couchbase-server","category-full-text-search","category-node-js","category-n1ql-query","tag-index"],"acf":[],"yoast_head":"\nFull Text Search (FTS) in Couchbase with the Node.js SDK<\/title>\n<meta name=\"description\" content=\"Learn how to use full text search in a Node.js application using the Node.js SDK for Couchbase Server and what all you should already have installed.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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