term用法
先看看term的定義，term是代表完全匹配，也就是精確查詢，搜索前不會再對搜索詞進行分詞拆解。
這里通過例子來說明，先存放一些數據：
{ "title": "love China", "content": "people very love China", "tags": ["China", "love"] } { "title": "love HuBei", "content": "people very love HuBei", "tags": ["HuBei", "love"] }
來使用term 查詢下：
{ "query": { "term": { "title": "love" } } }
結果是，上面的兩條數據都能查詢到：
{ "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 2, "max_score": 0.6931472, "hits": [ { "_index": "test", "_type": "doc", "_id": "8", "_score": 0.6931472, "_source": { "title": "love HuBei", "content": "people very love HuBei", "tags": ["HuBei","love"] } }, { "_index": "test", "_type": "doc", "_id": "7", "_score": 0.6931472, "_source": { "title": "love China", "content": "people very love China", "tags": ["China","love"] } } ] } }
發現，title里有關love的關鍵字都查出來了，但是我只想精確匹配 love China這個，按照下面的寫法看看能不能查出來：
{ "query": { "term": { "title": "love China" } } }
執行發現無數據，從概念上看，term屬於精確匹配，只能查單個詞。我想用term匹配多個詞怎么做？可以使用terms來：
{ "query": { "terms": { "title": ["love", "China"] } } }
查詢結果為：
{ "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 2, "max_score": 0.6931472, "hits": [ { "_index": "test", "_type": "doc", "_id": "8", "_score": 0.6931472, "_source": { "title": "love HuBei", "content": "people very love HuBei", "tags": ["HuBei","love"] } }, { "_index": "test", "_type": "doc", "_id": "7", "_score": 0.6931472, "_source": { "title": "love China", "content": "people very love China", "tags": ["China","love"] } } ] } }
發現全部查詢出來，為什么？因為terms里的[ ] 多個是或者的關系，只要滿足其中一個詞就可以。想要通知滿足兩個詞的話，就得使用bool的must來做，如下：
{ "query": { "bool": { "must": [ { "term": { "title": "love" } }, { "term": { "title": "china" } } ] } } }
可以看到，我們上面使用
china是小寫的。當使用的是大寫的
China 我們進行搜索的時候，發現搜不到任何信息。這是為什么了？title這個詞在進行存儲的時候，進行了分詞處理。我們這里使用的是默認的分詞處理器進行了分詞處理。我們可以看看如何進行分詞處理的？
分詞處理器
GET test/_analyze { "text" : "love China" }
結果為：
{ "tokens": [ { "token": "love", "start_offset": 0, "end_offset": 4, "type": "<ALPHANUM>", "position": 0 }, { "token": "china", "start_offset": 5, "end_offset": 10, "type": "<ALPHANUM>", "position": 1 } ] }
分析出來的為love和china的兩個詞。而term只能完完整整的匹配上面的詞，不做任何改變的匹配。所以，我們使用China這樣的方式進行的查詢的時候，就會失敗。稍后會有一節專門講解分詞器。
match 用法
先用 love China來匹配。
GET test/doc/_search { "query": { "match": { "title": "love China" } } }
結果是：
{ "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 2, "max_score": 1.3862944, "hits": [ { "_index": "test", "_type": "doc", "_id": "7", "_score": 1.3862944, "_source": { "title": "love China", "content": "people very love China", "tags": [ "China", "love" ] } }, { "_index": "test", "_type": "doc", "_id": "8", "_score": 0.6931472, "_source": { "title": "love HuBei", "content": "people very love HuBei", "tags": [ "HuBei", "love" ] } } ] } }
發現兩個都查出來了，為什么？因為match進行搜索的時候，會先進行分詞拆分，拆完后，再來匹配，上面兩個內容，他們title的詞條為： love china hubei ，我們搜索的為love China 我們進行分詞處理得到為love china ，並且屬於或的關系，只要任何一個詞條在里面就能匹配到。如果想 love 和 China 同時匹配到的話，怎么做？使用 match_phrase
match_phrase 用法
match_phrase 稱為短語搜索，要求所有的分詞必須同時出現在文檔中，同時位置必須緊鄰一致。
GET test/doc/_search { "query": { "match_phrase": { "title": "love china" } } }
結果為：
{ "took": 5, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 1, "max_score": 1.3862944, "hits": [ { "_index": "test", "_type": "doc", "_id": "7", "_score": 1.3862944, "_source": { "title": "love China", "content": "people very love China", "tags": [ "China", "love" ] } } ] } }