phpes短語精確搜索,Elasticsearch：在搜索引擎中如何實現完全匹配（內容精確。。。本?地址：在有搜索引擎之前，我們查?檔常使?順序匹配。?如要搜索"我的祖國是花園"，需要在?檔中順序掃描，找到完全匹配的?句。在有了搜索引擎后，我們對查詢語句做的處理就不?樣了。我們通常會先分詞，然后查找對應的詞條索引，最后得到評分由?到低的?檔列表。我?度以為沒法實現完全匹配了，直到?個硬需求的出現。花了?天時間，把完全匹配?搜索引擎的思維整理出來。簡要描述實現思路，字段按?字?詞的形式分詞，再利?短語查詢來搜索。ES中，可以實現?字?詞的的分詞器是NGram。它其實是?個上下?相連續字符的分詞?具，可以看官??檔中的例?。當我們將它min_gram和max_gram都設為1時，它會按?字?詞的形式分詞。?如“shinyke@189.cn”，分詞的結果是["s","h","i","n","y","k","e","@","1","8","9",".","c","n"]。/index_name/{"settings":{"analysis":{"analyzer":{"charSplit":{"type":"custom","tokenizer":"ngram_tokenizer"}},"tokenizer":{"ngram_tokenizer":{"type":"nGram","min_gram":"1","max_gram":"1","token_chars":["letter","digit","punctuation"]}}}

}}以上語句中，構建了?個名為“charSplit”的分析器。它使??個名為“ngram_tokenizer”的Ngram分詞器。可以?如下語句測試charSplit分析器，可以看到?字?詞的效果："測試語句"把這個分析器在mapping??起來：..."sender":{"type":"string","store":"yes","analyzer":"charSplit","fields":{"raw":{"type":"string","index":"not_analyzed"}},...接下來就可以?match_phrase來實現完全匹配查詢。/{index_name}/{type_name}/_search{"query":{"multi_match":{"query":"@189.cn","type":"phrase",//type指定為phrase"slop":0,//slop指定每個相鄰詞之間允許相隔多遠。此處設置為0，以實現完全匹配。"fields":["sender"],"analyzer":"charSplit",//分析器指定為charSplit"max_expansions":1}},

"highlight":{//測試?亮是否正常"pre_tags":[""],"post_tags":[""],"fragment_size":100,"number_of_fragments":2,"require_field_match":true,"fields":{"sender":{}}}}phrase查詢原始的作?是?來做短語查詢，它有?個重要的特點：有順序。我們利?了它匹配的有序性，限制slop為0，則可實現完全匹配查詢。以上語句返回的結果是:{"took":18,"timed_out":false,"_shards":{"total":9,"successful":9,"failed":0},"hits":{"total":1,"max_score":0.40239456,"hits":[{"_index":"index_name","_type":"type_name","_id":"AU9OLIGOZN4dLecgyoKp","_score":0.40239456,

"_source":{"sender":lt189.cn>,李X<189.cn>,秦X<189.cn>,劉X<189.cn>"},"highlight":{"sender":[lt@189.cn>,李X<@189.cn>,秦純X<@189.cn>,劉X<189773140"]}}]}}到此，就實現了完全匹配查詢。實際環境中?NGram做?字?詞