【发布时间】:2015-12-20 08:00:54
【问题描述】:
我正在尝试使用 function_score 中定义的不同函数修改来自正常查询的分数。
为了找出我的函数计算出的分数,我将“boost_mode”指定为“replace”。但是,这会使所有分数保持不变:都等于 1。
考虑以下查询:
{
"query": {
"function_score": {
"query": {
"terms": {
"name": ["men", "women"]
}
},
"score_mode": "avg",
"functions": [
{
"filter": {
"terms": {
"name": ["men","man"]
}
},
"weight": 2
}
],
"boost_mode": "replace"
}
},
"explain": true,
"from": 0
}
我希望在这里得到不同的分数,这取决于“姓名”字段是包含“男人”还是“男人”。此类文档肯定存在于索引中。
此外,如果我指定“解释”:true,我得到的解释中显示的分数与命中的 _score 字段中显示的分数不同:
{
"_shard":0,
"_node":"ro26nlDuTfiTaIlIgHqg4g",
"_index":"products10",
"_type":"product_basic",
"_id":"0c25fc90433481aac0cce62dd1a21e06",
"_score":1,
"_source":{
"category":[
"Chicago Blues",
"Blues",
"Styles",
"Digital Music"
],
"site_name":"www.amazon.com",
"name":"Who's That Women?",
"url":"http://www.amazon.com/dp/B001125F8I/",
"price":0.99,
"reviews":[
],
"breadcrumb":"Digital Music",
"in_stock":true,
"features":[
],
"pic_urls":[
"http://ecx.images-amazon.com/images/I/51CvgPMwtsL.jpg",
"http://ecx.images-amazon.com/images/I/51CvgPMwtsL.jpg"
],
"name_semantic_core":[
"Women ?",
"?"
],
"category_path":"/Chicago Blues/Blues/Styles/",
"visit_datetime":"2014-11-04T11:50:34.169779",
"detected_category":"Digital Music"
},
"_explanation":{
"value":1.2249949,
"description":"function score, no filter match, product of:",
"details":[
{
"value":1.2249949,
"description":"product of:",
"details":[
{
"value":2.4499898,
"description":"sum of:",
"details":[
{
"value":2.4499898,
"description":"weight(name:women in 6181332) [PerFieldSimilarity], result of:",
"details":[
{
"value":2.4499898,
"description":"score(doc=6181332,freq=1.0), product of:",
"details":[
{
"value":0.67790973,
"description":"queryWeight, product of:",
"details":[
{
"value":7.228071,
"description":"idf(docFreq=238699, maxDocs=120967660)"
},
{
"value":0.09378847,
"description":"queryNorm"
}
]
},
{
"value":3.6140356,
"description":"fieldWeight in 6181332, product of:",
"details":[
{
"value":1,
"description":"tf(freq=1.0), with freq of:",
"details":[
{
"value":1,
"description":"termFreq=1.0"
}
]
},
{
"value":7.228071,
"description":"idf(docFreq=238699, maxDocs=120967660)"
},
{
"value":0.5,
"description":"fieldNorm(doc=6181332)"
}
]
}
]
}
]
}
]
},
{
"value":0.5,
"description":"coord(1/2)"
}
]
},
{
"value":1,
"description":"queryBoost"
}
]
}
}
这里的解释显示“value”:1.2249949,而“_score”为1。
我做错了什么?如何获得使用 functinon_score 函数计算的实际分数[在与原始查询分数结合之前]?
【问题讨论】:
-
在您的示例中,该函数与任何文档都不匹配:
function score, no filter match,。此外,在使用replace时,从documentation 会发生以下情况:only function score is used, the query score is ignored。所以,情况是这样的:过滤器不匹配 - 所以不计算评分 - 并且replace将使查询分数被忽略并使用过滤器中的分数(它不存在,因为它没有'不匹配)。 -
而函数不匹配时,函数的默认值为
1。您可以通过"boost_mode": "sum"进行检查。我的看法是,这就是您看到分数为1的原因。 -
@AndreiStefan 提供的样本确实如此。该产品不匹配。但是对于匹配的产品,由于某种原因它仍然返回 1(请参阅有问题的更新)。
-
@AndreiStefan 嗯,然后当我将“score_mode”从“avg”更改为“multiply”时,我得到了有意义的结果:第一个得分为“2”,然后得分为“1”
-
是的,
sum也是如此。我想知道平均值是如何计算出来的……看起来不太对。
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