{"id":1523,"date":"2014-12-16T19:21:01","date_gmt":"2014-12-16T19:21:01","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=1523"},"modified":"2025-06-13T20:20:42","modified_gmt":"2025-06-14T03:20:42","slug":"caching-queries-couchbase-high-performance","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/pt\/caching-queries-couchbase-high-performance\/","title":{"rendered":"Consultas em cache no Couchbase para alto desempenho"},"content":{"rendered":"

A partir da vers\u00e3o 2.0, o servidor Couchbase oferece uma maneira eficiente de criar \u00edndices para documentos JSON por meio do conceito de exibi\u00e7\u00f5es.<\/span><\/p>\n

 <\/p>\n

Usando exibi\u00e7\u00f5es, \u00e9 poss\u00edvel definir \u00edndices prim\u00e1rios, \u00edndices compostos e agrega\u00e7\u00f5es que permitem:<\/span><\/p>\n

. consultar documentos em diferentes propriedades JSON<\/span><\/p>\n

. criar estat\u00edsticas e agregados<\/span><\/p>\n

 <\/p>\n

As visualiza\u00e7\u00f5es geram \u00edndices materializados, o que proporciona uma maneira r\u00e1pida e eficiente de executar consultas predefinidas.<\/span><\/p>\n

No entanto, no Couchbase 2.x, os \u00edndices s\u00e3o armazenados no disco e lidos do disco para cada consulta, o que tem algumas implica\u00e7\u00f5es de desempenho.<\/span><\/p>\n

No futuro, o Couchbase permitir\u00e1 o armazenamento em cache de \u00edndices no cache gerenciado de forma semelhante ao que \u00e9 feito para documentos JSON para acelerar as consultas.<\/span><\/p>\n

 <\/p>\n

Enquanto isso, este blog fornece um exemplo simples de como os resultados da consulta podem ser armazenados em cache no Couchbase para serem recuperados do cache em vez de serem servidos a partir do \u00edndice no disco.<\/span><\/p>\n

Isso \u00e9 \u00fatil para cen\u00e1rios em que uma consulta a um \u00edndice n\u00e3o precisa ser atualizada imediatamente (minutos ou mais s\u00e3o suficientes), mas \u00e9 lida com frequ\u00eancia (v\u00e1rias vezes por segundo). Nesse caso, os resultados da consulta ser\u00e3o calculados apenas de vez em quando com base nas necessidades do aplicativo e lidos do cache gerenciado no restante do tempo.<\/span><\/p>\n

Um bom exemplo de caso de uso para isso \u00e9 uma tabela de classifica\u00e7\u00e3o de jogos. Uma exibi\u00e7\u00e3o pode ser usada para criar um \u00edndice para as pontua\u00e7\u00f5es mais altas de um determinado jogo e essa exibi\u00e7\u00e3o pode ser consultada a cada poucos minutos (digamos, 5 minutos) e armazenada em cache no Couchbase Server. Todas as solicita\u00e7\u00f5es para a exibi\u00e7\u00e3o ser\u00e3o direcionadas ao valor armazenado em cache e, portanto, levar\u00e3o apenas alguns ms e n\u00e3o precisar\u00e3o de nenhuma consulta de \u00edndice no servidor.<\/span><\/p>\n

 <\/p>\n

Observe que o m\u00e9todo acima \u00e9 independente da atualiza\u00e7\u00e3o autom\u00e1tica dos \u00edndices. Por padr\u00e3o, cada \u00edndice no Couchbase \u00e9 atualizado a cada 5 segundos ou 5000 atualiza\u00e7\u00f5es, ambos ajust\u00e1veis por meio da API REST. Saiba mais sobre isso em: <\/span>https:\/\/www.couchbase.com\/docs\/couchbase-manual-2.1.0\/couchbase-views-operation-autoupdate.html<\/span><\/a><\/p>\n

 <\/p>\n

Isso significa que, embora o \u00edndice possa ser mantido atualizado, as consultas espec\u00edficas, que n\u00e3o precisam ser atualizadas, podem ser armazenadas em cache para aumentar a taxa de transfer\u00eancia e diminuir a lat\u00eancia. A \u00fanica ressalva \u00e9 que o tamanho m\u00e1ximo dos valores no Couchbase \u00e9 de 20 MB, portanto, as consultas em cache n\u00e3o devem ser usadas para conjuntos de resultados muito grandes, embora seja sempre poss\u00edvel dividir os resultados em v\u00e1rios valores em cache para conjuntos maiores.<\/span><\/p>\n

 <\/p>\n

Isso \u00e9 bastante simples de implementar. Vamos dar uma olhada em como podemos fazer isso em Java.<\/span><\/p>\n

 <\/p>\n

Usarei o banco de dados bee-sample, que vem com o servidor Couchbase. Se voc\u00ea ainda n\u00e3o o instalou, v\u00e1 para Settings (Configura\u00e7\u00f5es) e selecione beer-sample (amostra de cerveja) e clique em Create (Criar):<\/span><\/p>\n

<\/p>\n

Ele vem com uma visualiza\u00e7\u00e3o brewery_beer, que usarei para criar o exemplo de armazenamento em cache:<\/span><\/p>\n

 <\/p>\n

<\/p>\n

Agora vamos dar uma olhada em um aplicativo Java simples que pode ser usado para executar e armazenar em cache uma consulta e comparar com a execu\u00e7\u00e3o da consulta todas as vezes.<\/span><\/p>\n

 <\/p>\n

O c\u00f3digo Java abaixo, primeiro se conecta ao banco de dados de amostras de abelhas e:<\/span><\/p>\n

. executa a consulta 1 vez e a l\u00ea do cache n vezes ou<\/span><\/p>\n

. executa a consulta n vezes<\/span><\/p>\n

 <\/p>\n

Em ambos os casos, um cron\u00f4metro \u00e9 iniciado antes e depois para medir o tempo de execu\u00e7\u00e3o.<\/span><\/p>\n

 <\/p>\n

O c\u00f3digo \u00e9 muito simples, n\u00e3o usa par\u00e2metros para a consulta, mas usa includeDocs para recuperar todos os documentos JSON associados aos resultados da consulta em vez de apenas os IDs dos documentos.<\/span><\/p>\n

 <\/p>\n

Para saber mais sobre exibi\u00e7\u00f5es e consultas no Couchbase, leia: <\/span>https:\/\/www.couchbase.com\/docs\/couchbase-devguide-2.1.0\/indexing-querying-data.html<\/span><\/a><\/p>\n

O c\u00f3digo-fonte completo \u00e9:<\/span><\/p>\n

 <\/p>\n

\/\/ @author Alexis Roos<\/span><\/p>\n

pacote com.couchbase.dev.examples;<\/span><\/p>\n

 <\/p>\n

import com.couchbase.client.CouchbaseClient;<\/span><\/p>\n

import com.couchbase.client.protocol.views.*;<\/span><\/p>\n

 <\/p>\n

importar java.net.URI;<\/span><\/p>\n

importar java.util.LinkedList;<\/span><\/p>\n

importar java.util.List;<\/span><\/p>\n

 <\/p>\n

classe p\u00fablica CachedQuery {<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0public static void main(String args[]) {<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0List uris = new LinkedList();<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0uris.add(URI.create(\"https:\/\/127.0.0.1:8091\/pools\"));<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0CouchbaseClient client = null;<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0tente {<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0cliente = novo CouchbaseClient(uris, \"beer-sample\", \"\");<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0int requestCount = 100;<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0double t1 = System.currentTimeMillis();<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0View view = client.getView(\"beer\", \"brewery_beers\");<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Consulta = new Query();<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0query.setIncludeDocs(true).setLimit(10000);<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0query.setStale(Stale.FALSE);<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\/\/ Fazendo a consulta uma \u00fanica vez e armazenando-a em cache<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0ViewResponse result = client.query(view, query);<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0client.set(\"cachedBrewery_beersQuery\", 0, result.toString());<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\/\/ Uso do cache para solicita\u00e7\u00f5es subsequentes<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0for (int i = 0; i < requestCount - 1; i++) {<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0String cachedIndex = (String) client.get(\"cachedBrewery_beersQuery\");<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0}<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0double t2 = System.currentTimeMillis();<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0System.out.println(\"Teste com cache conclu\u00eddo em \" + (t2 - t1) \/ 1000 + \" segundos\");<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0t1 = System.currentTimeMillis();<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\/\/ Consultando todas as vezes<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0for (int i = 0; i < requestCount; i++) {<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0result = client.query(view, query);<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0}<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0t2 = System.currentTimeMillis();<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0System.out.println(\"O teste sem cache foi conclu\u00eddo em \" + (t2 - t1) \/ 1000 + \" segundos\");<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0cliente.shutdown();<\/span><\/p>\n

 <\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0} catch (Exception e) {<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0System.err.println(\"Erro ao conectar-se ao Couchbase: \" + e.getMessage());<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0System.exit(0);<\/span><\/p>\n

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0}<\/span><\/p>\n

\u00a0\u00a0\u00a0}<\/span><\/p>\n

}<\/span><\/p>\n

 <\/p>\n

A execu\u00e7\u00e3o do c\u00f3digo produz os dois resultados do teste, que para 100 consultas em s\u00e9rie produz:<\/span><\/p>\n

 <\/p>\n

Teste com cache conclu\u00eddo em 3,755 segundos<\/span><\/p>\n

O teste sem cache foi conclu\u00eddo em 19,835 segundos<\/span><\/p>\n

 <\/p>\n

N\u00e3o s\u00f3 o teste com cache \u00e9 muito mais r\u00e1pido, mas tamb\u00e9m requer menos recursos no servidor Couchbase.<\/span><\/p>\n

O gr\u00e1fico a seguir mostra a m\u00e9trica de opera\u00e7\u00f5es por segundo para o bucket de amostra de cerveja e o primeiro pequeno aumento corresponde ao teste com cache (essencialmente mapeando o n\u00famero de documentos para cervejarias e cervejas, pois a consulta \u00e9 executada apenas uma vez), enquanto o restante da curva maior mostra que a consulta foi executada muitas vezes e, portanto, resultou em muito mais opera\u00e7\u00f5es por segundo.<\/span><\/p>\n

 <\/p>\n

<\/p>\n

 <\/p>\n

\u00c9 f\u00e1cil usar o armazenamento em cache para consultar exibi\u00e7\u00f5es, e \u00e9 simples configurar um programa que consultar\u00e1 periodicamente a exibi\u00e7\u00e3o e armazenar\u00e1 o resultado no servidor Couchbase, onde ser\u00e1 armazenado em cache. Por sua vez, os aplicativos podem usar esse valor em cache para obter efici\u00eancia.<\/span><\/p>\n

Isso deve ser usado conforme apropriado, com base nos casos de uso do aplicativo.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Starting from version 2.0, Couchbase server offers a powerful way of creating indexes for JSON documents through the concept of views.   Using views, it is possible to define primary indexes, composite indexes and aggregations allowing to: . query documents […]<\/p>","protected":false},"author":15,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[9417,1812],"tags":[1239,1241],"ppma_author":[8994],"class_list":["post-1523","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-performance","category-n1ql-query","tag-caching","tag-views"],"acf":[],"yoast_head":"\nCaching Queries Results for High Performance | Couchbase<\/title>\n<meta name=\"description\" content=\"This blog provides examples of how query results can be cached into Couchbase to be retrieved from the cache instead of being served from index on disk.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/pt\/caching-queries-couchbase-high-performance\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Caching queries in Couchbase for high performance\" \/>\n<meta property=\"og:description\" content=\"This blog provides examples of how query results can be cached into Couchbase to be retrieved from the cache instead of being served from index on disk.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.couchbase.com\/blog\/pt\/caching-queries-couchbase-high-performance\/\" \/>\n<meta property=\"og:site_name\" content=\"The Couchbase Blog\" \/>\n<meta property=\"article:published_time\" content=\"2014-12-16T19:21:01+00:00\" \/>\n<meta property=\"article:modified_time\" 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