获取should子句匹配的计数

Question

我想计算

doc['_num_matches']

的值以在

script_score

中使用，它现在是一个假设字段，作为should子句匹配的计数，对于每个should子句匹配，将1添加到

doc['_num_matches']

。

例如

doc0: "banana"
doc0['_num_matches'] == 1

doc1: "apple apple apple apple apple apple banana"
doc1['_num_matches'] == 2

doc2: "apple banana cherry"
doc2['_num_matches'] == 3

{
    "query": {
        "function_score": {
            "query": {
                "bool": {
                    "should": [
                        {
                            "match": {
                                "content": {
                                    "query": "apple",
                                    "analyzer": "kuromoji"
                                }
                            }
                        },
                        {
                            "match": {
                                "content": {
                                    "query": "cherry",
                                    "analyzer": "kuromoji"
                                }
                            }
                        },
                        {
                            "match": {
                                "content": {
                                    "query": "banana",
                                    "analyzer": "kuromoji"
                                }
                            }
                        }
                    ],
                    "minimum_should_match": "2<80%"
                }
            },
            "functions": [
                {
                    "script_score": {
                        "script": {
                            "source": "_score * Math.log(1 + doc['_num_matches'].value)"
                        }
                    }
                }
            ],
            "boost_mode": "replace"
        }
    },
    "size": 200
}

Answer 1

如果您选择正确的映射，这很容易

映射

PUT /term_count_score
{
    "mappings": {
        "properties": {
            "text": {
                "type": "text",
                "fields": {
                    "terms": {
                        "type": "text",
                        "analyzer": "whitespace_lowercase_trim_remove_duplicates_analyzer",
                        "fielddata": true
                    }
                }
            }
        }
    },
    "settings": {
        "analysis": {
            "analyzer": {
                "whitespace_lowercase_trim_remove_duplicates_analyzer": {
                    "tokenizer": "whitespace",
                    "filter": [
                        "lowercase",
                        "trim"
                    ]
                }
            }
        }
    }
}

您的文件

PUT /term_count_score/_bulk
{"create":{"_id":1}}
{"text": "banana banana"}
{"create":{"_id":2}}
{"text": "apple apple apple apple apple apple banana"}
{"create":{"_id":3}}
{"text":"cherry banana apple"}

查询

GET /term_count_score/_search?filter_path=hits.hits.fields,hits.hits._score,hits.hits._id
{
    "query": {
        "function_score": {
            "query": {
                "match_all": {}
            },
            "functions": [
                {
                    "script_score": {
                        "script": "doc['text.terms'].length"
                    }
                }
            ]
        }
    },
    "script_fields": {
        "text_terms": {
            "script": "doc['text.terms']"
        }
    }
}

我将

script_fields

添加到查询中以测试索引

回应

{
    "hits" : {
        "hits" : [
            {
                "_id" : "3",
                "_score" : 3.0,
                "fields" : {
                    "text_terms" : [
                        "apple",
                        "banana",
                        "cherry"
                    ]
                }
            },
            {
                "_id" : "2",
                "_score" : 2.0,
                "fields" : {
                    "text_terms" : [
                        "apple",
                        "banana"
                    ]
                }
            },
            {
                "_id" : "1",
                "_score" : 1.0,
                "fields" : {
                    "text_terms" : [
                        "banana"
                    ]
                }
            }
        ]
    }
}