进阶-第18__深度探秘搜索技术_基于slop参数实现近似匹配以及原理剖析和相关实验
尝鲜
|
GET /forum/article/_search { "query": { "match_phrase": { "title": { "query": "java spark", "slop": 1 } } } } 结果： { "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 0, "max_score": null, "hits": [] } } |
slop（移动）的含义是什么？
query string，搜索文本，中的几个term，要经过几次移动才能与一个document匹配，这个移动的次数，就是slop
slop实际移动举例
实际举例，一个query string经过几次移动之后可以匹配到一个document，然后设置slop
hello world, java is very good, spark is also very good.
java spark，match phrase，搜不到
如果我们指定了slop，那么就允许java spark进行移动，来尝试与doc进行匹配
java is very good spark is
java spark
java --> spark 移动一位
java --> spark 移动两位
java --> spark 移动三位
这里的slop，就是3，因为java spark这个短语，spark移动了3次，就可以跟一个doc匹配上了
slop的含义，不仅仅是说一个query string terms移动几次，跟一个doc匹配上。而是说，一个query string terms，最多可以移动几次去尝试跟一个doc匹配上
slop，设置的是3，那么就ok
GET /forum/article/_search
{
"query": {
"match_phrase": {
"title": {
"query": "spark data",
"slop": 3
}
}
}
}
就可以把刚才那个doc匹配上，那个doc会作为结果返回
但是如果slop设置的是2，那么java spark，spark最多只能移动2次，此时跟doc是匹配不上的，那个doc是不会作为结果返回的
做实验，验证slop的含义
实验一
|
GET /forum/article/_search { "query": { "match_phrase": { "content": { "query": "spark data", "slop": 3 } } } } 结果： { "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 0, "max_score": null, "hits": [] } } |
实验二
|
GET /forum/article/_search { "query": { "match_phrase": { "content": { "query": "spark data", "slop": 2 } } } } 结果 { "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 0, "max_score": null, "hits": [] } } |
实验三
|
GET /forum/article/_search { "query": { "match_phrase": { "content": { "query": "spark data", "slop": 3 } } } } 结果： { "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 1, "max_score": 0.21824157, "hits": [ { "_index": "forum", "_type": "article", "_id": "5", "_score": 0.21824157, "_source": { "articleID": "DHJK-B-1395-#Ky5", "userID": 3, "hidden": false, "postDate": "2017-03-01", "tag": [ "elasticsearch" ], "tag_cnt": 1, "view_cnt": 10, "title": "this is spark blog", "content": "spark is best big data solution based on scala ,an programming language similar to java spark", "sub_title": "haha, hello world", "author_first_name": "Tonny", "author_last_name": "Peter Smith" } } ] } } |
Spark is best big data solution based on scala ,an programming language similar to java spark
spark data
--> data 移动一位
--> data 移动两位
spark --> data 移动三位
实验四增强
|
GET /forum/article/_search { "query": { "match_phrase": { "content": { "query": "data spark", "slop": 5 } } } } 结果： { "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 1, "max_score": 0.154366, "hits": [ { "_index": "forum", "_type": "article", "_id": "5", "_score": 0.154366, "_source": { "articleID": "DHJK-B-1395-#Ky5", "userID": 3, "hidden": false, "postDate": "2017-03-01", "tag": [ "elasticsearch" ], "tag_cnt": 1, "view_cnt": 10, "title": "this is spark blog", "content": "spark is best big data solution based on scala ,an programming language similar to java spark", "sub_title": "haha, hello world", "author_first_name": "Tonny", "author_last_name": "Peter Smith" } } ] } } |
spark is best big data
data spark
--> data/spark 移动一位
spark àdata 移动两位
spark --> data 移动三位
spark --> data 移动四位
spark --> data 移动五位
slop搜索下，关键词离的越近，relevance score就会越高，做实验说明。。。
|
{ "took": 4, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 3, "max_score": 1.3728157, "hits": [ { "_index": "forum", "_type": "article", "_id": "2", "_score": 1.3728157, "_source": { "articleID": "KDKE-B-9947-#kL5", "userID": 1, "hidden": false, "postDate": "2017-01-02", "tag": [ "java" ], "tag_cnt": 1, "view_cnt": 50, "title": "this is java blog", "content": "i think java is the best programming language", "sub_title": "learned a lot of course", "author_first_name": "Smith", "author_last_name": "Williams", "new_author_last_name": "Williams", "new_author_first_name": "Smith" } }, { "_index": "forum", "_type": "article", "_id": "5", "_score": 0.5753642, "_source": { "articleID": "DHJK-B-1395-#Ky5", "userID": 3, "hidden": false, "postDate": "2017-03-01", "tag": [ "elasticsearch" ], "tag_cnt": 1, "view_cnt": 10, "title": "this is spark blog", "content": "spark is best big data solution based on scala ,an programming language similar to java spark", "sub_title": "haha, hello world", "author_first_name": "Tonny", "author_last_name": "Peter Smith", "new_author_last_name": "Peter Smith", "new_author_first_name": "Tonny" } }, { "_index": "forum", "_type": "article", "_id": "1", "_score": 0.28582606, "_source": { "articleID": "XHDK-A-1293-#fJ3", "userID": 1, "hidden": false, "postDate": "2017-01-01", "tag": [ "java", "hadoop" ], "tag_cnt": 2, "view_cnt": 30, "title": "this is java and elasticsearch blog", "content": "i like to write best elasticsearch article", "sub_title": "learning more courses", "author_first_name": "Peter", "author_last_name": "Smith", "new_author_last_name": "Smith", "new_author_first_name": "Peter" } } ] } } |
实验
|
GET /forum/article/_search { "query": { "match_phrase": { "content": { "query": "java best", "slop": 15 } } } } 结果 { "took": 3, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 2, "max_score": 0.65380025, "hits": [ { "_index": "forum", "_type": "article", "_id": "2", "_score": 0.65380025, "_source": { "articleID": "KDKE-B-9947-#kL5", "userID": 1, "hidden": false, "postDate": "2017-01-02", "tag": [ "java" ], "tag_cnt": 1, "view_cnt": 50, "title": "this is java blog", "content": "i think java is the best programming language", "sub_title": "learned a lot of course", "author_first_name": "Smith", "author_last_name": "Williams", "new_author_last_name": "Williams", "new_author_first_name": "Smith" } }, { "_index": "forum", "_type": "article", "_id": "5", "_score": 0.07111243, "_source": { "articleID": "DHJK-B-1395-#Ky5", "userID": 3, "hidden": false, "postDate": "2017-03-01", "tag": [ "elasticsearch" ], "tag_cnt": 1, "view_cnt": 10, "title": "this is spark blog", "content": "spark is best big data solution based on scala ,an programming language similar to java spark", "sub_title": "haha, hello world", "author_first_name": "Tonny", "author_last_name": "Peter Smith", "new_author_last_name": "Peter Smith", "new_author_first_name": "Tonny" } } ] } } |
其实，加了slop的phrase match，就是proximity match，近似匹配
1、java spark，短语，doc，phrase match
2、java spark，可以有一定的距离，但是靠的越近，越先搜索出来，proximity match
移动搜索的短语，以达到文档的内容
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