小编典典

如何获得Elasticsearch文档中每个单词的总数?

elasticsearch

我搜索了这个问题,但找不到任何有用的答案。我想获取文档中每个单词的总数,例如,我的索引中有一些推文,并且有一条推文中写着这样的内容:“这里太无聊了,我想去我的家,甜蜜的家”。查询应返回如下响应:

It:1
is:1
so:1
boring:1
here:1
I:1
want:1
to:2
go:1
my:1
home:2
sweet:1

有可能这样做吗?


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2020-06-22

共1个答案

小编典典

您正在寻找term vectors利用分析仪的。这样做时,您可以定义所需的任何分析器,即阻止分析器将单词转换为根/普通形式。查看文档以获取更多详细信息。

在:

POST so/_close
PUT so/_settings
{
  "settings": {
    "analysis":{ 
      "analyzer": {
        "my_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": ["lowercase", "my_stemmer"]
        }
      },
      "filter": {
        "my_stemmer": {
          "type": "stemmer",
          "name": "english"
        }
      }
    }
  }
}
POST so/_open
PUT so/t1/_mapping
{
  "t1": {
    "properties": {
      "tweet": {
        "type": "string",
        "store": true,
        "index_analyzer": "my_analyzer"
      }
    }
  }
}
POST so/t1/1
{"tweet": "It is so boring here I want to go to my home sweet home. So I'm bored"}

出:

{
   "_index": "so",
   "_type": "t1",
   "_id": "1",
   "_version": 2,
   "found": true,
   "term_vectors": {
      "tweet": {
         "field_statistics": {
            "sum_doc_freq": 13,
            "doc_count": 1,
            "sum_ttf": 17
         },
         "terms": {
            "bore": {
               "term_freq": 2,
               ...
            },
            "go": {
               "term_freq": 1,
               ...
            },
            "here": {
               "term_freq": 1,
               ...
            },
            "home": {
               "term_freq": 2,
               ...
            },
            "i": {
               "term_freq": 1,
               ...
            },
            "i'm": {
               "term_freq": 1,
               ...
            },
            "is": {
               "term_freq": 1,
               ...
            },
            "it": {
               "term_freq": 1,
               ...
            },
            "my": {
               "term_freq": 1,
               ...
            },
            "so": {
               "term_freq": 2,
               ...
            },
            "sweet": {
               "term_freq": 1,
               ...
            },
            "to": {
               "term_freq": 2,
               ...
            },
            "want": {
               "term_freq": 1,
               ...
            }
         }
      }
   }
}
2020-06-22