Elasticsearch的DSL之 term and match

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记录学习ES的DSL的一些比较重要的概念和方法。

term VS match

首先要说的是，一个doc进入ES被索引，哪些字段(fields)被索引是可以自定义的。默认，ES会对所有的fields进行索引。

PUT /my_index{  "mappings": {    "my_type": {      "properties": {        "status_code": {          "type": "string",          "index": "not_analyzed"        }      }    }  }}

这是个简单的mapping, 有个status_code字段，类型是string, index的方式是“not_analyzed”。 ES中某个字段的index方式有三种值：no/not_analyzed/analyzed，对应的意思是：

no = > 该字段不进入index，即不可对该字段进行query。

not_analyzed => 该字段作为一个term进入index,不进行分词等analyse操作。对除string类型之外的fields, 这个是默认的。对string类型的字段，默认要进行分词的，除非指定不进行分词(即not_analyzed) 。

analyzed =》只对string类型的field有效，且是默认的。通过analyzer, 该field会被切分成若干的分词(terms),

再来说，term和match

term是用来进行分词精确匹配的(The term query finds documents that contain the exact term specified in the inverted index.)

match是用来进行全文检索的（full-text search）。

看下面的一个例子，就能够很清楚的知道二者的区别了。例子来自https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-term-query.html

myindex下的一个类型是my_type的mapping:

PUT my_index{  "mappings": {    "my_type": {      "properties": {        "full_text": {          "type":  "string"         },        "exact_value": {          "type":  "string",          "index": "not_analyzed"         }      }    }  }}PUT my_index/my_type/1{  "full_text":   "Quick Foxes!",   "exact_value": "Quick Foxes!"  }

The full_text field is analyzed by default.

The exact_value field is set to be not_analyzed.

The full_text inverted index will contain the terms: [quick, foxes].

The exact_value inverted index will contain the exact term: [Quick Foxes!].

Now, compare the results for the term query and the match query:

(1)GET my_index/my_type/_search{  "query": {    "term": {      "exact_value": "Quick Foxes!"    }  }}(2)GET my_index/my_type/_search{  "query": {    "term": {      "full_text": "Quick Foxes!"     }  }}(3)GET my_index/my_type/_search{  "query": {    "term": {      "full_text": "foxes"     }  }}(4)GET my_index/my_type/_search{  "query": {    "match": {      "full_text": "Quick Foxes!"     }  }}

This query matches because the exact_value field contains the exact term Quick Foxes!.

This query does not match, because the full_text field only contains the terms quick andfoxes. It does not contain the exact term Quick Foxes!.

A term query for the term foxes matches the full_text field.

This match query on the full_text field first analyzes the query string, then looks for documents containing quick or foxes or both.

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