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 video card and requests highlighting on the fields name,features .

 

http://localhost:8983/solr/select/?wt=json&indent=on&q=*:*&fl=name&facet=true&facet.field=cat&facet.field=inStock

facet:refine their search results based on the returned categories.

the facet counts generated are for the complete set of documents that match the query.

返回的结果类似于：

"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 ipod and shows prices below and above 100 by using range queries on the price field.

http://localhost:8983/solr/select/?wt=json&indent=on&q=ipod&fl=name&facet=true&facet.query=price:[0+TO+100]&facet.query=price:[100+TO+*]

显示结果如下：

 "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 (manufacturedate_dt field) for each year between 2004 and 2010.

http://localhost:8983/solr/select/?wt=json&indent=on&q=*:*&fl=name,manufacturedate_dt&facet=true&facet.date=manufacturedate_dt&facet.date.start=2004-01-01T00:00:00Z&facet.date.end=2010-01-01T00:00:00Z&facet.date.gap=%2b1YEAR

显示结果如下：

"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）。