solr学习小结
solr 查询参数：各条件间以'&'分隔
q:查询
fl:返回已储存的内容，control what stored fields are returned。例如：q=video&fl=*,score
sort:排序，eg: q=video&sort=score asc,price desc&fl=name,id,price
wt:返回的数据类型，eg:q=video&wt=json
?
例子：http://localhost:8983/solr/select/?wt=json&indent=on&q=video+card&fl=name,id&hl=true&hl.fl=name,features
searches for "facet_counts":{ "facet_queries":{}, "facet_fields":{"cat":[ "electronics",16, "memory",6, "card",2, "connector",2, "software",2, "camera",1, "printer",1, "scanner",1],"inStock":[ "true",14, "false",4]}, "facet_dates":{}}}
?
Solr can also generate counts for arbitrary queries. The following example queries for "facet_counts":{ "facet_queries":{"price:[0 TO 100]":2,"price:[100 TO *]":1}, "facet_fields":{}, "facet_dates":{}}}
?
?
One can even facet by date ranges. This example requests counts for the manufacture date ("facet_counts":{ "facet_queries":{}, "facet_fields":{}, "facet_dates":{"manufacturedate_dt":{ "2004-01-01T00:00:00Z":0, "2005-01-01T00:00:00Z":2, "2006-01-01T00:00:00Z":8, "2007-01-01T00:00:00Z":0, "2008-01-01T00:00:00Z":0, "2009-01-01T00:00:00Z":0, "gap":"+1YEAR", "end":"2010-01-01T00:00:00Z"}}}}?
Text fields are typically indexed by breaking the field into words and applying various transformations such as lowercasing, removing plurals, or stemming to increase relevancy. The same text transformations are normally applied to any queries in order to match what is indexed.
文本域的索引通常是通过分词，再把各词转为小写，去除复数形式，去除词的状态（现在时，过去时）。
?
?
?
