如果我有这样的数据:
{"field1":"x", "field2":".."}
{"field1":"x", "field2":".."}
{"field1":"y", "field2":".."}
{"field1":"y", "field2":".."}
{"field1":"y", "field2":".."}
使用简单的group=true&group.field=field1&group.limit=0
我得到的结果如下:
{
"responseHeader":{..}
"grouped":{
"field1": {
"matches": 5,
"groups": [
{"groupValue": "x", "doclist":{"numFound": 2, ...}}
{"groupValue": "y", "doclist":{"numFound": 3, ...}}
]
}
}
}
使用此功能,我知道为每个groupValue
(numFound
)找到的文档数量。问题是我需要按降序对结果组进行排序,这对于任何一种排序都是不可能的(简单sort=numFound
会导致异常,说字段numFound
不存在和组。 sort会对每个组内的文档进行排序。)
是否有相当于使用facets的方法,我可以按计数对结果进行排序?
答案 0 :(得分:1)
您可以尝试:
http://localhost:8983/solr/your_core/select?facet.field=field1&facet.sort=count&facet.limit=-1&facet=on&indent=on&q=*:*&rows=0&start=0&wt=json
结果如下:
{
"responseHeader":{
"status":0,
"QTime":17,
"params":{
"q":"*:*",
"facet.field":"field1",
"indent":"on",
"start":"0",
"rows":"0",
"facet":"on",
"wt":"json"}},
"response":{"numFound":225364,"start":0,"docs":[]
},
"facet_counts":{
"facet_queries":{},
"facet_fields":{
"field1":[
"x",113550,
"y",111814]},
"facet_ranges":{},
"facet_intervals":{},
"facet_heatmaps":{}
}
}
刚刚使用Solr 6.3.0测试。
有关详情,请查看Solr documentation中的相关部分。
如果要同时计算可用构面的数量,可以使用Solr stats
组件(因为字段的类型为数字,字符串或日期)。
但请记住,可能会出现服务器性能和内存开销问题。
运行如下的查询:
http://localhost:8983/solr/your_core/select?facet.field=field1&facet.sort=count&facet.limit=10&facet=true&indent=on&q=*:*&rows=0&start=0&wt=json&stats=true&stats.field={!cardinality=true}field1
响应类似于:
{
"responseHeader":{
"status":0,
"QTime":614,
"params":{
"facet.limit":"10",
"q":"*:*",
"facet.field":"field1",
"indent":"on",
"stats":"true",
"start":"0",
"rows":"0",
"facet":"true",
"wt":"json",
"facet.sort":"count",
"stats.field":"{!cardinality=true}field1"}},
"response":{"numFound":2336315,"start":0,"docs":[]
},
"facet_counts":{
"facet_queries":{},
"facet_fields":{
"field1":[
"Value1",708116,
"Value2",607088,
"Value3",493949,
"Value4",314433,
"Value5",104478,
"Value6",41099,
"Value7",28879,
"Value8",18767,
"Value9",9308,
"Value10",4545]},
"facet_ranges":{},
"facet_intervals":{},
"facet_heatmaps":{}},
"stats":{
"stats_fields":{
"field1":{
"cardinality":27}}}}
有关stats
的详情,请查看here。