我正在将我的elasticsearch从5.6升级到8.9，我有一个查询，其中我按权重字段和_score排序。分配给数据的分数存在差异，因此给出了不同的结果顺序。
谁能帮我找到问题和解决方案相同
查询-

POST /auto-complete/_search?typed_keys=true
{
    "size": 5,
    "query": {
        "bool": {
            "should": [
                {
                    "match_phrase_prefix": {
                        "suggestion": {
                            "query": "the"
                        }
                    }
                },
                {
                    "match": {
                        "suggestion.analyzed": {
                            "fuzziness": "AUTO",
                            "operator": "and",
                            "query": "the"
                        }
                    }
                }
            ]
        }
    },
    "sort": [
        {
            "weight": {
                "order": "desc"
            }
        },
        {
            "_score": {
                "order": "desc"
            }
        }
    ]
}

字符串
在Elasticsearch 5.6数据上，

{
  "took": 129,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 4858,
    "max_score": null,
    "hits": [
      {
        "_index": "auto-complete",
        "_type": "default",
        "_id": "The Thelma Hoop Earrings",
        "_score": 6.3522644,
        "_source": {
          "suggestion": "The Thelma Hoop Earrings",
          "weight": 1
        },
        "sort": [
          1,
          6.3522644
        ]
      },
      {
        "_index": "auto-complete",
        "_type": "default",
        "_id": "The Theresa Ring",
        "_score": 6.3522644,
        "_source": {
          "suggestion": "The Theresa Ring",
          "weight": 1
        },
        "sort": [
          1,
          6.3522644
        ]
      },
      {
        "_index": "auto-complete",
        "_type": "default",
        "_id": "The Theodora Ring",
        "_score": 6.337865,
        "_source": {
          "suggestion": "The Theodora Ring",
          "weight": 1
        },
        "sort": [
          1,
          6.337865
        ]
      },
      {
        "_index": "auto-complete",
        "_type": "default",
        "_id": "The Thea Ring",
        "_score": 6.337865,
        "_source": {
          "suggestion": "The Thea Ring",
          "weight": 1
        },
        "sort": [
          1,
          6.337865
        ]
      },
      {
        "_index": "auto-complete",
        "_type": "default",
        "_id": "The Theor Band For Him",
        "_score": 5.7033815,
        "_source": {
          "suggestion": "The Theor Band For Him",
          "weight": 1
        },
        "sort": [
          1,
          5.7033815
        ]
      }
    ]
  }
}

型
在ElasticSearch 8.9上，它是-

{
  "took": 28,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 4874,
      "relation": "eq"
    },
    "max_score": null,
    "hits": [
      {
        "_index": "auto-complete",
        "_id": "The Theodora Ring",
        "_score": 8.927014,
        "_source": {
          "suggestion": "The Theodora Ring",
          "weight": 1
        },
        "sort": [
          1,
          8.927014
        ]
      },
      {
        "_index": "auto-complete",
        "_id": "The Theresa Ring",
        "_score": 8.927014,
        "_source": {
          "suggestion": "The Theresa Ring",
          "weight": 1
        },
        "sort": [
          1,
          8.927014
        ]
      },
      {
        "_index": "auto-complete",
        "_id": "The Thea Ring",
        "_score": 8.927014,
        "_source": {
          "suggestion": "The Thea Ring",
          "weight": 1
        },
        "sort": [
          1,
          8.927014
        ]
      },
      {
        "_index": "auto-complete",
        "_id": "The Thelma Hoop Earrings",
        "_score": 7.9907713,
        "_source": {
          "suggestion": "The Thelma Hoop Earrings",
          "weight": 1
        },
        "sort": [
          1,
          7.9907713
        ]
      }
    ]
  }
}

型
Elasticsearch 5.6的Map文件是-

curl -X PUT "localhost:9201/auto-complete?pretty" -H 'Content-Type: application/json' -d'
{ 
"mappings" : 
{
  "default": {
    "properties": {
      "suggestion": {
        "type": "text",
        "fields": {
          "analyzed": {
            "type": "text",
            "analyzer": "nGram_analyzer",
            "search_analyzer": "whitespace"
          }
        }
      },
      "weight": {
        "type": "integer"
      }
    }
  }
}, 
"settings" : 
{
  "number_of_shards": 1,
  "number_of_replicas": 1,
  "index": {
    "analysis": {
      "analyzer": {
        "nGram_analyzer": {
          "type": "custom",
          "tokenizer": "whitespace",
          "filter": [
            "lowercase",
            "asciifolding",
            "nGram_filter"
          ]
        }
      },
      "filter": {
        "nGram_filter": {
          "type": "nGram",
          "min_gram": 2,
          "max_gram": 20,
          "token_chars": [
            "letter",
            "digit",
            "punctuation",
            "symbol"
          ]
        }
      }
    }
  }
}
}'

型
Elasticsearch 8.9的Map是-

curl -X PUT "localhost:9201/auto-complete?pretty" -H 'Content-Type: application/json' -d'
{ 
"mappings" : 
{
  "properties": {
    "suggestion": {
      "type": "text",
      "fields": {
        "analyzed": {
          "type": "text",
          "analyzer": "nGram_analyzer",
          "search_analyzer": "whitespace"
        }
      }
    },
    "weight": {
      "type": "integer"
    }
  }
}, 
"settings" : 
{
  "number_of_shards": 1,
  "number_of_replicas": 1,
  "max_ngram_diff" : 18,
  "index": {
    "analysis": {
      "analyzer": {
        "nGram_analyzer": {
          "type": "custom",
          "tokenizer": "whitespace",
          "filter": [
            "lowercase",
            "asciifolding",
            "nGram_filter"
          ]
        }
      },
      "filter": {
        "nGram_filter": {
          "type": "ngram",
          "min_gram": 2,
          "max_gram": 20,
          "token_chars": [
            "letter",
            "digit",
            "punctuation",
            "symbol"
          ]
        }
      }
    }
  }
}}

型