C# Elasticsearch按分数筛选
我找不到类似的问题。要么我做错了什么,要么我不知道如何搜索 我的索引就是这样 例如,用户搜索“c001”,我查看search_all_字段并在两个文档中找到它。(所有搜索关键字“c”和“001”的通配符查询) 但第二个是无用的。因为第一个与项目号匹配。这更有价值。 第二个字段与第一组字段匹配。这就没那么值钱了。 我必须过滤它 但另一方面,有人搜索“yyy102”,然后它只发生在第一组和第二组字段中。 所以我不能过滤它 两次去弹性边得分是昂贵的。但我怎样才能做到这一点呢C# Elasticsearch按分数筛选,c#,
elasticsearch,nest,C#,
elasticsearch,Nest,我找不到类似的问题。要么我做错了什么,要么我不知道如何搜索 我的索引就是这样 例如,用户搜索“c001”,我查看search_all_字段并在两个文档中找到它。(所有搜索关键字“c”和“001”的通配符查询) 但第二个是无用的。因为第一个与项目号匹配。这更有价值。 第二个字段与第一组字段匹配。这就没那么值钱了。 我必须过滤它 但另一方面,有人搜索“yyy102”,然后它只发生在第一组和第二组字段中。 所以我不能过滤它 两次去弹性边得分是昂贵的。但我怎样才能做到这一点呢 public class
public class items
{
public string item_no { get; set; }
public string category { get; set; }
public int campaign { get; set; }
public int in_stock { get; set; }
// Next properties only include [a-z0-9]. Not any other characters
public string search_item_no { get; set; }
public string search_group_one { get; set; }
public string search_group_two { get; set; }
public string search_description { get; set; }
public string search_all_fields { get; set; } /* search_item_no + search_group_one + search_group_two + search_description and something else */
}
public class ClassForScore
{
public int id { get; set; }
public string item_no { get; set; }
}
item_no # category # campaign # in_stock # search_item_no # search_group_one # search_group_two # search_description # search_all_fields
p-C-001 # cat1 # 1 # 1 # pc001 # aaaa@bbb@ccc # kkkkk@llllllll # red@metal@light # pc001@aaaa@bbb@ccc@kkkkk@llllllll@red@metal@light
p-F-002 # cat1 # 1 # 1 # pf002 # ck001@www@zza # yyy@rrrr@mmplp # bold@plastic@ss # pf002@ck001@www@zza@yyy@rrrr@mmplp@bold@plastic@ss
p-SW102 # cat2 # 0 # 1 # psw102 # psw102@777@ooo # yyy@rrrr@mmplp # bold@plastic@cc # psw102@777@ooo@www@zza@yyy@rrrr@mmplp@bold@plastic@cc
QueryContainer queryContainsOr=new WildcardQuery(){Field=“score\u all\u fields”,Value=“*yyy*”};
queryContainsOr |=新的通配符查询(){Field=“score_all_fields”,Value=“*102*”};
QueryContainer queryEqualsOr=newtermquery(){Field=“category”,Value=“cat1”};
queryEqualsOr |=新术语查询(){Field=“category”,Value=“cat2”};
QueryContainer queryEqualsAnd=newtermquery(){Field=“campaign”,Value=1};
queryEqualsAnd&=newtermquery(){Field=“in_stock”,Value=1};
QueryContainer mainQuery=queryContainsOr&queryEqualsAnd&queryEqualsOr;
Func fo=funcScoreParam(新的ClassForCore(),filterItemNo,filterGroupOne,filterGroupTwo,filterDescription,mainQuery);
ISearchResponse srcSkor=elasticClient.Search(s=>s
.RequestConfiguration(r=>r.DisableDirectStreaming())
.查询(fo)
.尺寸(100)
);
IReadOnlyCollection lstSkor=srcSkor.Hits;
双重的dblSkorAvg=0;
//一些计算。。
//.....
Func fo2=funcScoreParam(新的ClassForCore(),filterItemNo,filterGroupOne,filterGroupTwo,filterDescription,mainQuery);
ISearchResponse srcResult=elasticClient.Search(s=>s
.RequestConfiguration(r=>r.DisableDirectStreaming())
.从(0)
.尺寸(100)
.Sort(S=>S.Descending(SortSpecialField.Score)。升序(r=>r.item_no))
.MinScore(dblSkorAvg)
.查询(fo2)
);
私有函数funcScoreParam(T nesne、QueryContainer filterItemNo、QueryContainer filterGroupOne、QueryContainer filterGroupTwo、QueryContainer filterDescription、QueryContainer mainQuery),其中T:class
{
返回新函数(q=>q
.FunctionScore(fsc=>fsc
.BoostMode(函数BoostMode.Sum)
.ScoreMode(FunctionScoreMode.Sum)
.函数(fu=>fu
.重量(w=>w
.重量(1000)
.Filter(wf=>wf
.Bool(bb=>bb
.Must(filterItemNo))
))
.重量(w=>w
.重量(100)
.Filter(wf=>wf
.Bool(bb=>bb
.Must(filterGroupOne))
))
.重量(w=>w
.重量(100)
.Filter(wf=>wf
.Bool(bb=>bb
.Must(过滤器组二))
))
.重量(w=>w
.重量(50)
.Filter(wf=>wf
.Bool(bb=>bb
.Must(过滤器描述))
))
)
.Query(q2=>q2
.Bool(b=>b
.Should(mainQuery))
)
));
}
QueryContainer queryContainsOr = new WildcardQuery() { Field = "score_all_fields", Value = "*yyy*" };
queryContainsOr |= new WildcardQuery() { Field = "score_all_fields", Value = "*102*" };
QueryContainer queryEqualsOr = new TermQuery() { Field = "category", Value = "cat1" };
queryEqualsOr |= new TermQuery() { Field = "category", Value = "cat2" };
QueryContainer queryEqualsAnd = new TermQuery() { Field = "campaign", Value = 1 };
queryEqualsAnd &= new TermQuery() { Field = "in_stock", Value = 1 };
QueryContainer mainQuery = queryContainsOr & queryEqualsAnd & queryEqualsOr;
Func<QueryContainerDescriptor<ClassForScore>, QueryContainer> fo = funcScoreParam(new ClassForScore(), filterItemNo, filterGroupOne, filterGroupTwo, filterDescription, mainQuery);
ISearchResponse<ClassForScore> srcSkor = elasticClient.Search<ClassForScore>(s => s
.RequestConfiguration(r => r.DisableDirectStreaming())
.Query(fo)
.Size(100)
);
IReadOnlyCollection<IHit<ClassForScore>> lstSkor = srcSkor.Hits;
double? dblSkorAvg = 0;
// Some calculation..
//.....
Func<QueryContainerDescriptor<items>, QueryContainer> fo2 = funcScoreParam(new ClassForScore(), filterItemNo, filterGroupOne, filterGroupTwo, filterDescription, mainQuery);
ISearchResponse<items> srcResult = elasticClient.Search<items>(s => s
.RequestConfiguration(r => r.DisableDirectStreaming())
.From(0)
.Size(100)
.Sort(S => S.Descending(SortSpecialField.Score).Ascending(r => r.item_no))
.MinScore(dblSkorAvg)
.Query(fo2)
);
private Func<QueryContainerDescriptor<T>, QueryContainer> funcScoreParam<T>(T nesne, QueryContainer filterItemNo, QueryContainer filterGroupOne, QueryContainer filterGroupTwo, QueryContainer filterDescription, QueryContainer mainQuery) where T : class
{
return new Func<QueryContainerDescriptor<T>, QueryContainer>(q => q
.FunctionScore(fsc => fsc
.BoostMode(FunctionBoostMode.Sum)
.ScoreMode(FunctionScoreMode.Sum)
.Functions(fu => fu
.Weight(w => w
.Weight(1000)
.Filter(wf => wf
.Bool(bb => bb
.Must(filterItemNo))
))
.Weight(w => w
.Weight(100)
.Filter(wf => wf
.Bool(bb => bb
.Must(filterGroupOne))
))
.Weight(w => w
.Weight(100)
.Filter(wf => wf
.Bool(bb => bb
.Must(filterGroupTwo))
))
.Weight(w => w
.Weight(50)
.Filter(wf => wf
.Bool(bb => bb
.Must(filterDescription))
))
)
.Query(q2 => q2
.Bool(b => b
.Should(mainQuery))
)
));
}