ElasticSearch關鍵字匹配向量

首先，對不起，如果我問的是愚蠢的，但我對彈性搜索很陌生。這是我需要做的：我有一組關鍵字，我需要在索引的每個檔案中搜索它們。這是映射：

{
  "resumes": {
    "mappings": {
      "properties": {
        "text": {
          "type": "text",
          "fields": {
            "keyword": {
              "type": "keyword",
              "ignore_above": 256
            }
          }
        },
        "timestamp": {
          "type": "date"
        }
      }
    }
  }
}

知道了這一點，我需要在每個檔案中搜索關鍵字陣列中的所有單詞，并且對于簡歷索引中的每個檔案，如果在檔案中找不到該單詞，它將回傳一個向量，如果是，則回傳 1成立。

例如。

keywords = ["javascript", "html", "python"]
doc1 = "Hello there, I've only programmed in python."
doc2 = "Hello there, I've only programmed in python and javascript."
doc3 = "Hello there, I've only programmed in python and javascript. Im now learning html"

搜索結果將類似于：

{
  "doc1": [0, 0, 1], // because it contains the word python
  "doc2": [1, 0, 1], // because it contains both python and javascript
  "doc3": [1, 1, 1]  // because it contains all words in the keyword vector
}

甚至可以單獨使用彈性搜索來做到這一點嗎？我正在用 Python 撰寫所有這些代碼，但我認為如果我用 Python 本身填充這些代碼，那么效率會比彈性搜索能做到的要低得多。

還沒有嘗試太多，因為我什至不太了解 Elastic Search 的功能。我已經搜索了很多，但我什至不知道從哪里開始......

uj5u.com熱心網友回復：

在 elasticsearch 中使用腳本并不健康，因為它們不具備執行性。我設法做你想做的事，但我警告你性能問題。

在“vector_field”欄位中，您有您的矩陣。

POST idx_teste/_doc 
{
  "description": "Hello there, I've only programmed in python."
}

POST idx_teste/_doc 
{
  "description": "Hello there, I've only programmed in python and javascript."
}

POST idx_teste/_doc 
{
  "description": "Hello there, I've only programmed in python and javascript. Im now learning html"
}

GET idx_teste/_search
{
  "_source": "*", 
  "query": {
    "terms": {
      "description": [
        "javascript","html","python"
      ]
    }
  }, 
   "script_fields": {
     "custom_field": {
       "script": {
         "source":  """
              def vector = new ArrayList();
              for(int i=0; i< params.keywords.size(); i  ){
                String text = doc['description.keyword'].value;
                if(text.contains(params.keywords[i])) {
                  vector.add(1);
                } else {
                  vector.add(0);
                }
              }
              return vector;
          """,
          "params": {
            "keywords" :[
                "javascript","html","python"
              ]
          }
       }
     }
   }
}

回復：

"hits": [
      {
        "_index": "idx_teste",
        "_id": "oIyiQ4QBgXg8h_rc0Ny3",
        "_score": 1,
        "_source": {
          "description": "Hello there, I've only programmed in python."
        },
        "fields": {
          "vector_field": [
            0,
            0,
            1
          ]
        }
      },
      {
        "_index": "idx_teste",
        "_id": "oYypQ4QBgXg8h_rcH9wU",
        "_score": 1,
        "_source": {
          "description": "Hello there, I've only programmed in python and javascript."
        },
        "fields": {
          "vector_field": [
            1,
            0,
            1
          ]
        }
      },
      {
        "_index": "idx_teste",
        "_id": "ooypQ4QBgXg8h_rcJ9y2",
        "_score": 1,
        "_source": {
          "description": "Hello there, I've only programmed in python and javascript. Im now learning html"
        },
        "fields": {
          "vector_field": [
            1,
            1,
            1
          ]
        }
      }
    ]

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