{"id":7153,"date":"2019-07-03T18:54:18","date_gmt":"2019-07-04T01:54:18","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=7153"},"modified":"2021-07-13T00:46:05","modified_gmt":"2021-07-13T07:46:05","slug":"a-glimpse-of-fts-performance-improvements-in-6-5-0-part-1","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/pt\/a-glimpse-of-fts-performance-improvements-in-6-5-0-part-1\/","title":{"rendered":"Uma vis\u00e3o geral dos aprimoramentos de desempenho do FTS na vers\u00e3o 6.5.0 - Parte 1"},"content":{"rendered":"

Ever since the nimbler, refined `<\/span>queimar<\/span><\/a>` indexing format released in Couchbase 6.0.0, the FTS team has been pretty excited about the future optimisation potential unlocked with the newer indexing scheme. With the 6.5.0 release, we have essentially embarked on a never ending journey of optimising and tuning the performance of the Full Text Search engine.<\/span><\/p>\n

 <\/p>\n

Deixe-me compartilhar algumas informa\u00e7\u00f5es sobre as otimiza\u00e7\u00f5es interessantes que estamos introduzindo na pr\u00f3xima vers\u00e3o 6.5.0.\u00a0<\/span><\/p>\n

 <\/p>\n

Consultas geogr\u00e1ficas <\/b><\/h4>\n

O FTS oferece suporte a dois tipos de consultas geogr\u00e1ficas <\/span>Dist\u00e2ncia de pontos e ret\u00e2ngulo delimitado<\/span><\/a>. Desde o in\u00edcio do recurso, n\u00e3o tivemos a chance de revisar e aprimorar esse recurso, embora fosse quase certo que a implementa\u00e7\u00e3o da consulta precisasse de melhorias em termos de utiliza\u00e7\u00e3o da mem\u00f3ria e da CPU. A boa not\u00edcia \u00e9 que, de todos os aprimoramentos de desempenho futuros na vers\u00e3o 6.5.0, vimos os maiores ganhos com as altera\u00e7\u00f5es geogr\u00e1ficas.<\/span><\/p>\n

 <\/p>\n

Oportunidade<\/b><\/h5>\n

Como parte da an\u00e1lise do alto uso de mem\u00f3ria pelas consultas geogr\u00e1ficas, ficou claro que h\u00e1 um enorme potencial de ajuste de desempenho que ainda n\u00e3o foi explorado. No caso dos tipos de consulta de dist\u00e2ncia de ponto e ret\u00e2ngulo delimitado, o mecanismo de indexa\u00e7\u00e3o (<\/span>sangrar<\/span><\/a>) precisa descobrir o intervalo de pontos geogr\u00e1ficos a serem pesquisados (termos candidatos) que qualificam os crit\u00e9rios de pesquisa a partir dos par\u00e2metros de consulta fornecidos. O Bleve deriva esses termos geogr\u00e1ficos candidatos por meio de determinadas etapas matem\u00e1ticas.<\/span><\/p>\n

Mas ele n\u00e3o estava fazendo nenhuma filtragem dos termos geogr\u00e1ficos candidatos gerados matematicamente. Em outras palavras, uma amplifica\u00e7\u00e3o n\u00e3o intencional do espa\u00e7o de pesquisa estava ocorrendo em segundo plano. E isso estava desencadeando a cria\u00e7\u00e3o de muitos iteradores de pesquisa de termos desnecess\u00e1rios ou irrelevantes (por exemplo, termos que nem sequer existem no \u00edndice), o que leva a muitos objetos tempor\u00e1rios internos para gerenciar e, al\u00e9m disso, adiciona uma grande sobrecarga ao coletor de lixo.\u00a0<\/span><\/p>\n

Resposta<\/b><\/h5>\n

Otimizamos esse caso aplicando uma filtragem de termos geogr\u00e1ficos que basicamente valida os pontos geogr\u00e1ficos gerados matematicamente quanto \u00e0 sua exist\u00eancia no dicion\u00e1rio de termos e os qualifica somente se estiverem presentes no dicion\u00e1rio de termos. Essa abordagem reduziu significativamente o n\u00famero de pontos geogr\u00e1ficos\/termos candidatos que est\u00e3o sendo pesquisados no \u00edndice invertido e, portanto, melhorou os n\u00fameros de lat\u00eancia e taxa de transfer\u00eancia para consultas geogr\u00e1ficas.<\/span><\/p>\n

Recompensa<\/b><\/h5>\n

Isso resultou em uma melhoria de at\u00e9 <\/span>6X<\/b> redu\u00e7\u00e3o de lat\u00eancia para consultas geogr\u00e1ficas em nossos benchmarks internos.<\/span><\/p>\n

 <\/p>\n

Consultas difusas <\/b><\/h4>\n

Em pr\u00e9 <\/span>queimar<\/span><\/a> dias, quando um <\/span>fuzzy\/edit-distance<\/span><\/a> Quando a consulta \u00e9 recebida, o mecanismo de indexa\u00e7\u00e3o examina todos os termos indexados em rela\u00e7\u00e3o ao campo determinado na consulta para calcular a dist\u00e2ncia de edi\u00e7\u00e3o e descobrir se o termo atual est\u00e1 dentro da dist\u00e2ncia de edi\u00e7\u00e3o solicitada com o termo da consulta. E se ele se qualificar para esse crit\u00e9rio de dist\u00e2ncia de edi\u00e7\u00e3o, ele procurar\u00e1 o termo no \u00edndice invertido para buscar a lista de documentos em que o termo aparece e os detalhes necess\u00e1rios, conforme exigido pela consulta. (vetores de termos, valores de documentos <\/span>etc<\/span><\/a>)\u00a0<\/span><\/p>\n

 <\/p>\n

O recente formato de indexa\u00e7\u00e3o scorch usa FiniteStateTransducers(<\/span>FST<\/span><\/a>) para implementar o Dicion\u00e1rio de Termos, que tem o seguinte <\/span>DFA<\/span><\/a> propriedade. Isso nos ajudou a aprimorar a abordagem novata para encontrar os termos candidatos em uma determinada dist\u00e2ncia de edi\u00e7\u00e3o da consulta.<\/span><\/p>\n

 <\/p>\n

A abordagem \u00e9 criar um <\/span>L<\/b>evenshtein <\/span>A<\/b>utomaton(<\/span>LA<\/span><\/a>) para o termo dado na consulta de dist\u00e2ncia de edi\u00e7\u00e3o. Esse LA \u00e9 um DFA que tem a propriedade de corresponder a todos os termos que est\u00e3o, no m\u00e1ximo, a uma dist\u00e2ncia de edi\u00e7\u00e3o de um determinado \"d\" na consulta. E esse LA DFA seria ent\u00e3o feito para se juntar ou fazer uma interse\u00e7\u00e3o com o corpus de termos indexados\/dicion\u00e1rio de termos original (FST DFA) para filtrar os termos candidatos que precisam ser eventualmente pesquisados como parte da consulta.<\/span><\/p>\n

 <\/p>\n

Oportunidade<\/b><\/h5>\n

At\u00e9 o lan\u00e7amento da vers\u00e3o 6.0, est\u00e1vamos criando o LA DFA novamente a cada consulta recebida, e essa parte da constru\u00e7\u00e3o do LA DFA acabou sendo desgastante em termos de uso de mem\u00f3ria e velocidade da constru\u00e7\u00e3o do DFA.<\/span><\/p>\n

Resposta<\/b><\/h5>\n

Inspirado no original <\/span>papel<\/span><\/a> e a postagem no blog - <\/span>Levenshtein<\/span><\/a>A constru\u00e7\u00e3o mais recente do aut\u00f4mato de Levenshtein adota uma abordagem de duas etapas. Na primeira etapa, ele pr\u00e9-computa um DFA param\u00e9trico para um conjunto de dist\u00e2ncias de edi\u00e7\u00e3o predefinidas* e essa parte \u00e9 completamente independente da string de consulta e, portanto, pode ser pr\u00e9-computada. Na segunda etapa, esse DFA param\u00e9trico \u00e9 usado para calcular o DFA LA por consulta. Isso faz com que a constru\u00e7\u00e3o do DFA seja bastante r\u00e1pida e f\u00e1cil de usar na mem\u00f3ria.<\/span><\/p>\n

Recompensa<\/b><\/h5>\n

Os benchmarks do Go micro mostraram que a implementa\u00e7\u00e3o mais recente \u00e9 capaz de <\/span>5X<\/b> mais r\u00e1pido e <\/span>12X<\/b> melhor no uso da mem\u00f3ria. E, em nossos testes internos de desempenho, isso trouxe at\u00e9 ~50%<\/strong> melhorias no rendimento da consulta.<\/span><\/p>\n

 <\/p>\n

Fico feliz em ver que voc\u00ea rolou a tela at\u00e9 aqui.\u00a0<\/span><\/p>\n

Vou fazer uma parada abrupta aqui para facilitar sua aten\u00e7\u00e3o e guardar as hist\u00f3rias restantes para a Parte 2. A pr\u00f3xima parte abordar\u00e1 os ganhos de desempenho com a ado\u00e7\u00e3o do gRPC no FTS, bem como com consultas como intervalo num\u00e9rico, prefixo, curinga etc.<\/span><\/p>\n

 <\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0… Parte 2<\/a><\/em><\/strong><\/h5>\n

 <\/p>\n

{Dist\u00e2ncias de edi\u00e7\u00e3o pr\u00e9-definidas => no momento, o FTS suporta dist\u00e2ncias de edi\u00e7\u00e3o de at\u00e9 2, ou seja, apenas 1 e 2.\u00a0<\/span><\/p>\n

A principal raz\u00e3o para isso \u00e9 que, em qualquer corpus de documentos de tamanho razo\u00e1vel, haver\u00e1 muitos termos que correspondem a uma dist\u00e2ncia de edi\u00e7\u00e3o > 2 do termo de consulta. Portanto, qualquer pesquisa adicional no \u00edndice se torna muito intensiva em termos de recursos, al\u00e9m de diminuir a relev\u00e2ncia da pesquisa}.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Ever since the nimbler, refined `scorch` indexing format released in Couchbase 6.0.0, the FTS team has been pretty excited about the future optimisation potential unlocked with the newer indexing scheme. With the 6.5.0 release, we have essentially embarked on a […]<\/p>","protected":false},"author":26446,"featured_media":5952,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1816,2165],"tags":[2378],"ppma_author":[9075],"class_list":["post-7153","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-couchbase-server","category-full-text-search","tag-6-5"],"acf":[],"yoast_head":"\nA Glimpse of FTS Performance Improvements in 6.5.0 - Part 1 - The Couchbase Blog<\/title>\n<meta name=\"description\" content=\"FTS performance improvements on geo queries, fuzzy\/edit distance queries, levenshtein automaton, FSTs, bounded rectangle, point distance queries.\" \/>\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\/a-glimpse-of-fts-performance-improvements-in-6-5-0-part-1\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A Glimpse of FTS Performance Improvements in 6.5.0 - 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