elasticsearch - ElasticSearch-嵌套在过滤器中的script_score不影响得分-为什么？

Question

使用的属性:

{
 "mappings": {
   "properties": {
     "attribute_must_1": {
       "type": "nested"
     },
     "attribute_1": {
       "type": "nested"
     },
     "attribute_2": {
       "type": "nested"
     },
   }
 }

}
输入测试文件:

POST _bulk
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":9},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":9},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":8},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":7},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":11},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":5},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":10},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":6},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":7},"attribute_2":{"id":3}}
{"index":{"_index":"scores","_type":"_doc"}}
{"attribute_must_1":{"id":1},"attribute_1":{"id":7},"attribute_2":{"id":3}}

实际查询:

q = {
    "size": 10,
    "query": {
        "function_score": {
            "query": {
    "bool": {
      "filter": [
      ],
      "must": [
        {
          "nested": {
            "path": "attribute_must_1",
            "query": {
              "term": {
                "attribute_must_1.id": "1"
              }
            }
          }
        }
      ]
    }
  },
  "boost": 1,
  "functions": [
    {
      "filter": {
        "nested": {
          "path": "attribute_1",
          "query": {
              "script_score": {
                "query": {
                      "match_all": {}
                  },
                  "script": {
                      "source": "decayNumericLinear(params.origin, params.scale, params.offset, params.decay, doc['attribute_1.id'].value)",
                      "params": {
                          "origin": 10,
                          "scale": 5,
                          "decay": 2,
                          "offset": 0
                      }
                  }
              }
          },
        }
      },
      "weight": 30
    },
    {"filter": {"nested": {"path": "attribute_2", "query": {"term": {"attribute_2.id": "3"}}}}, "weight": 70},

  ],
  "score_mode": "sum",
  "boost_mode": "replace"
 }
},
"sort": [
  "_score",
   {
     "date_deposit": {
     "order": "desc"
   }
   }
   ]
  }

我正在尝试添加一个带有嵌套字段“attribute_1”的新过滤器，我想在该字段中计算实际值与所有其他文档的值之间的距离，但对得分没有影响，我可以看到:
对于找到的attribute_1:
文件= [9、9、9、10、9、9、4、9、3、9]
我得到了(从2个属性中获得30％和70％的权重之和):
分数= [100，100，100，100，100，100，100，100，100，100]
因此它看起来相当二进制，而应该是线性函数。
我想要的是这样的:
用于找到的文档值:[10、9、8、3、10]
输入值为10->我希望具有:
得分(以百分比表示):[100％，90％，80％，30％，100％]
我希望得到一个简单的分数，其输出范围为0-100％，但包括以下方式来自多个属性(attribute_1，attribute_2，...)的部分分数:

基于距离(即0％到30％之间的任何值)的线性分数中来自attribute_1的

分数

来自attribute_2的

得分是0％或70％(字词查询)

我尝试了各种变体，但没有任何效果-正确的做法是什么？我的印象是 filter查询无法以某种方式执行script_scores ...
我希望有人可以帮助我吗？
巨大的THNX!

Answer 1

I have tried different variations, but nothing works - what is the correct way of doing that? I have the impression that the filter query can't do script_scores somehow ...

你是对的。如 documentation中所述-“在过滤器上下文中，查询子句回答问题“此文档与该查询子句匹配吗？”答案很简单，是或否- 不会计算分数。过滤器上下文主要用于过滤结构化数据，例如。
我建议您不要在需要评分的查询中使用过滤器。