拥有这些文件:
{ "created_at" : "2017-07-31T20:30:14-04:00", "description" : null, "height" : 3213, "id" : "1", "tags" : [ { "confidence" : 65.48948436785749, "tag" : "beach" }, { "confidence" : 57.31950504425406, "tag" : "sea" }, { "confidence" : 43.58207236617374, "tag" : "coast" }, { "confidence" : 35.6857910950816, "tag" : "sand" }, { "confidence" : 33.660057321079655, "tag" : "landscape" }, { "confidence" : 32.53252312423727, "tag" : "sky" } ], "width" : 5712, "color" : "#0C0A07", "boost_multiplier" : 1 }
和
{ "created_at" : "2017-07-31T20:43:17-04:00", "description" : null, "height" : 4934, "id" : "2", "tags" : [ { "confidence" : 84.09123410403951, "tag" : "mountain" }, { "confidence" : 56.412795342449456, "tag" : "valley" }, { "confidence" : 48.36547551196872, "tag" : "landscape" }, { "confidence" : 40.51100450186575, "tag" : "mountains" }, { "confidence" : 33.14263528292239, "tag" : "sky" }, { "confidence" : 31.064394646169404, "tag" : "peak" }, { "confidence" : 29.372, "tag" : "natural elevation" } ], "width" : 4016, "color" : "#FEEBF9", "boost_multiplier" : 1 }
我想获得基于每个标签的置信度值计算的_score。例如,如果您搜索“ mountain”,则显然应该仅返回ID为1的文档;如果您搜索“ landscape”,则得分2应该高于1,因为景观对2的置信度高于1(48.36 vs 33.66)。如果您搜索“ coast landscape”,则此时间得分1应该高于2,因为doc 1在标签数组中同时包含了Coast和Landscape。我还想将分数与“ boost_multiplier”相乘,以增强某些文档的性能。
我在Elasticsearch中发现了这个问题:文档中具有自定义得分字段的影响力得分
但是,当我尝试接受的解决方案(我在我的ES服务器中启用脚本)时,无论搜索词如何,它都返回带有_score 1.0的两个文档。这是我尝试过的查询:
{ "query": { "nested": { "path": "tags", "score_mode": "sum", "query": { "function_score": { "query": { "match": { "tags.tag": "coast landscape" } }, "script_score": { "script": "doc[\"confidence\"].value" } } } } } }
我还尝试了@yahermann在注释中建议的内容,将“ script_score”替换为“ field_value_factor”:{“ field”:“ confidence”},结果仍然相同。知道为什么它会失败,或者有更好的方法吗?
只是为了全面了解,这是我使用的映射定义:
{ "mappings": { "photo": { "properties": { "created_at": { "type": "date" }, "description": { "type": "text" }, "height": { "type": "short" }, "id": { "type": "keyword" }, "tags": { "type": "nested", "properties": { "tag": { "type": "string" }, "confidence": { "type": "float"} } }, "width": { "type": "short" }, "color": { "type": "string" }, "boost_multiplier": { "type": "float" } } } }, "settings": { "number_of_shards": 1 } }
更新 在下面@Joanna的答案之后,我尝试了查询,但是实际上,无论我在匹配查询,coast,foo,bar中放置什么,它总是返回两个文档都带有_score1.0的文档,我在elasticsearch2.4上进行了尝试Docker中的.6、5.3、5.5.1。这是我得到的答复:
HTTP/1.1 200 OK Content-Type: application/json; charset=UTF-8 Content-Length: 1635 {"took":24,"timed_out":false,"_shards":{"total":5,"successful":5,"failed":0},"hits":{"total":2,"max_score":1.0,"hits":[{"_index":"my_index","_type":"my_type","_id":"2","_score":1.0,"_source":{ "created_at" : "2017-07-31T20:43:17-04:00", "description" : null, "height" : 4934, "id" : "2", "tags" : [ { "confidence" : 84.09123410403951, "tag" : "mountain" }, { "confidence" : 56.412795342449456, "tag" : "valley" }, { "confidence" : 48.36547551196872, "tag" : "landscape" }, { "confidence" : 40.51100450186575, "tag" : "mountains" }, { "confidence" : 33.14263528292239, "tag" : "sky" }, { "confidence" : 31.064394646169404, "tag" : "peak" }, { "confidence" : 29.372, "tag" : "natural elevation" } ], "width" : 4016, "color" : "#FEEBF9", "boost_multiplier" : 1 } },{"_index":"my_index","_type":"my_type","_id":"1","_score":1.0,"_source":{ "created_at" : "2017-07-31T20:30:14-04:00", "description" : null, "height" : 3213, "id" : "1", "tags" : [ { "confidence" : 65.48948436785749, "tag" : "beach" }, { "confidence" : 57.31950504425406, "tag" : "sea" }, { "confidence" : 43.58207236617374, "tag" : "coast" }, { "confidence" : 35.6857910950816, "tag" : "sand" }, { "confidence" : 33.660057321079655, "tag" : "landscape" }, { "confidence" : 32.53252312423727, "tag" : "sky" } ], "width" : 5712, "color" : "#0C0A07", "boost_multiplier" : 1 } }]}}
UPDATE-2 我在SO上发现了这一点:Elasticsearch:带有“boost_mode”的“function_score”:“replace”忽略了函数得分
它的基本含义是,如果函数不匹配,则返回1。这是有道理的,但我正在对同一文档运行查询。令人困惑。
最后更新 最终我发现了问题,我很愚蠢。ES101,如果您发送GET请求以搜索api,它将返回所有得分为1.0的文档:)您应该发送POST请求…非常感谢@Joanna,它运行良好!
您可以尝试使用此查询-它结合了得分:confidence和boost_multiplier字段:
confidence
boost_multiplier
{ "query": { "function_score": { "query": { "bool": { "should": [{ "nested": { "path": "tags", "score_mode": "sum", "query": { "function_score": { "query": { "match": { "tags.tag": "landscape" } }, "field_value_factor": { "field": "tags.confidence", "factor": 1, "missing": 0 } } } } }] } }, "field_value_factor": { "field": "boost_multiplier", "factor": 1, "missing": 0 } } } }
当我搜索coast字词时-它返回:
coast
id=1
"_score": 100.27469
当我搜索landscape术语时-它返回两个文档:
landscape
id=2
由于id=2具有较高confidence字段值的文档,其得分更高。
当我搜索coast landscape术语时-它返回两个文档:
coast landscape
尽管id=2具有的文档具有较高的confidence字段值,但是具有的文档id=1具有匹配的单词,因此得分更高。通过更改"factor": 1参数的值,您可以决定confidence应多少影响结果。
"factor": 1
当我为一个新文档建立索引时,会发生更有趣的事情:假设它与具有的文档几乎相同,id=2但是我设置了"boost_multiplier" : 4和"id": 3:
"boost_multiplier" : 4
"id": 3
{ "created_at" : "2017-07-31T20:43:17-04:00", "description" : null, "height" : 4934, "id" : "3", "tags" : [ ... { "confidence" : 48.36547551196872, "tag" : "landscape" }, ... ], "width" : 4016, "color" : "#FEEBF9", "boost_multiplier" : 4 }
使用coast landscapeterm 运行相同的查询将返回三个文档:
id=3
尽管的文档id=3只有一个匹配的单词(landscape),但其boost_multiplier值大大提高了评分。在此处,"factor": 1您还可以使用决定该值应增加多少分值,并"missing": 0确定如果没有索引该字段应发生什么。
"missing": 0