我需要从ElasticSearch指数获得了随机抽样,即发出查询检索从加权概率定索引一些文档Wj/ΣWi(这里Wj是行的权重j,并Wj/ΣWi在此查询所有文件的权重的总和)。
Wj/ΣWi
Wj
j
当前,我有以下查询:
GET products/_search?pretty=true {"size":5, "query": { "function_score": { "query": { "bool":{ "must": { "term": {"category_id": "5df3ab90-6e93-0133-7197-04383561729e"} } } }, "functions": [{"random_score":{}}] } }, "sort": [{"_score":{"order":"desc"}}] }
它从选定类别中随机返回5个项目。每个项目都有一个字段weight。所以,我可能必须使用
weight
"script_score": { "script": "weight = data['weight'].value / SUM; if (_score.doubleValue() > weight) {return 1;} else {return 0;}" }
作为描述在这里。
我有以下问题:
非常感谢你的帮助!
万一它对任何人都有帮助,这就是我最近实施加权改组的方式。
在此示例中,我们对公司进行了洗牌。每个公司都有一个介于0到100之间的“ company_score”。通过这种简单的加权改组,得分为100的公司出现在首页的可能性是得分为20的公司的5倍。
json_body = { "sort": ["_score"], "query": { "function_score": { "query": main_query, # put your main query here "functions": [ { "random_score": {}, }, { "field_value_factor": { "field": "company_score", "modifier": "none", "missing": 0, } } ], # How to combine the result of the two functions 'random_score' and 'field_value_factor'. # This way, on average the combined _score of a company having score 100 will be 5 times as much # as the combined _score of a company having score 20, and thus will be 5 times more likely # to appear on first page. "score_mode": "multiply", # How to combine the result of function_score with the original _score from the query. # We overwrite it as our combined _score (random x company_score) is all we need. "boost_mode": "replace", } } }