Elasticsearch---學習記錄(4)
阿新 • • 發佈:2018-11-24
15.記錄------查詢體
使用GET進行查詢,可以帶入查詢引數.
curl -XGET http://172.16.150.149:29200/facebook,twitter/_search?pretty -d ' {"from":5,"size":3} ' { "took" : 1, "timed_out" : false, "_shards" : { "total" : 4, "successful" : 4, "failed" : 0 }, "hits" : { "total" : 8, "max_score" : 1.0, "hits" : [ { "_index" : "facebook", "_type" : "blog", "_id" : "AWZ668ZcHFL4sAFl7IMI", "_score" : 1.0, "_source" : { "title" : "website", "text" : "blog is making", "date" : "2018/1016" } }...
16.記錄------匹配字首解析查詢
給定一個首字母,進行匹配.
-XGET http://172.16.150.149:29200/facebook,twitter/_search?pretty -d ' {"query":{ "match_phrase_prefix":{ "text":"blog i" }}}' { "took" : 1, "timed_out" : false, "_shards" : { "total" : 4, "successful" : 4, "failed" : 0 }, "hits" : { "total" : 3, "max_score" : 1.0, "hits" : [ { "_index" : "facebook", "_type" : "blog", "_id" : "AWZ67I_dHFL4sAFl7IMJ", "_score" : 1.0, "_source" : { "title" : "website", "text" : "blog is making", "date" : "2018/1016" } ...
官方強烈推薦再設定match_phrase_prefix
來設定後續匹配的個數.
curl -XGET http://172.16.150.149:29200/facebook,twitter/_search?pretty -d ' {"query":{ "match_phrase_prefix":{ "text":"blog i" }}}' { "took" : 1, "timed_out" : false, "_shards" : { "total" : 4, "successful" : 4, "failed" : 0 }, "hits" : { "total" : 3, "max_score" : 1.0, "hits" : [ { "_index" : "facebook", "_type" : "blog", "_id" : "AWZ67I_dHFL4sAFl7IMJ", "_score" : 1.0, "_source" : { "title" : "website", "text" : "blog is making", "date" : "2018/1016" } ...
17.記錄------多匹配查詢與_score的進一步瞭解
curl -XGET http://172.16.150.149:29200/facebook,twitter/_search?pretty -d '
{"query":{
"multi_match":{
"query":"blog is ",
"fields":["title","text"]}}}'
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 4,
"successful" : 4,
"failed" : 0
},
"hits" : {
"total" : 4,
"max_score" : 0.41762865,
"hits" : [ {
"_index" : "facebook",
"_type" : "blog",
"_id" : "AWZ67I_dHFL4sAFl7IMJ",
"_score" : 0.41762865,
"_source" : {
"title" : "website",
"text" : "blog is making",
"date" : "2018/1016"
}
...
對_score
欄位的進一步瞭解
_score
欄位代表著被查詢的文章與查詢的相關性程度,分越高,自然相關度就越高.
查詢結果,往往都按照_score
進行降序顯示.
es的評分機制,是建立於lucene的評分基礎之上,並且不限於其評分機制.
lucene評分機制
TF/IDF(詞頻/逆文件頻率)演算法
其計算文件得分需要考慮若干的影響因素
文件權重(document boost)
欄位權重(field boost)
協調因子(coord)
逆文件頻率(inverse document frequency)
長度範數(length norm)
詞頻
查詢函式(query norm)
參考詳見還包括了Lucene預設與實際評分公式