In Elasticsearch Document关于功能得分查询显示代码的说明如下
GET /_search
{
"query": {
"function_score": {
"query": { "match_all": {} },
"boost": "5",
"functions": [
{
"filter": { "match": { "test": "bar" } },
"random_score": {},
"weight": 23
},
{
"filter": { "match": { "test": "cat" } },
"weight": 42
}
],
"max_boost": 42,
"score_mode": "max",
"boost_mode": "multiply",
"min_score" : 42
}
}
}
我将此查询写到object initializer syntax
var searchRequest = new SearchRequest<ProductType>
{
Query = new FunctionScoreQuery()
{
Query = new MatchAllQuery {},
Boost = 5,
Functions = new List<IScoreFunction>
{
Filters...?
},
MaxBoost = 42,
ScoreMode = FunctionScoreMode.Max,
BoostMode = FunctionBoostMode.Max,
MinScore = 42
}
};
如何在函数中构建过滤器?
IScoreFunction
界面仅允许ExponentialDecayFunction
,GaussDateDecayFunction
,LinearGeoDecayFunction
,FieldValueFactorFunction
,RandomScoreFunction
,WeightFunction
,{{ 1}}
答案 0 :(得分:1)
Functions是IScoreFunction
的集合。在示例JSON中,第一个函数是随机得分函数,第二个函数是权重函数。链接的Query DSL示例包含不同功能的示例,这是与上面的JSON匹配的示例
var client = new ElasticClient();
var searchRequest = new SearchRequest<ProductType>
{
Query = new FunctionScoreQuery()
{
Query = new MatchAllQuery { },
Boost = 5,
Functions = new List<IScoreFunction>
{
new RandomScoreFunction
{
Filter = new MatchQuery
{
Field = "test",
Query = "bar"
},
Weight = 23
},
new WeightFunction
{
Filter = new MatchQuery
{
Field = "test",
Query = "cat"
},
Weight = 42
}
},
MaxBoost = 42,
ScoreMode = FunctionScoreMode.Max,
BoostMode = FunctionBoostMode.Multiply,
MinScore = 42
}
};
var searchResponse = client.Search<ProductType>(searchRequest);