Elasticsearch高手进阶篇(7)
深度探秘搜索技术_在案例中体验如何手动控制全文检索结果的精准度
1、为帖子数据增加标题字段
POST /waws/article/_bulk
{ "update": { "_id": "1"} }
{ "doc" : {"title" : "this is java and elasticsearch blog"}}
{ "update": { "_id": "2"} }
{ "doc" : {"title" : "this is java blog"}}
{ "update": { "_id": "3"} }
{ "doc" : {"title" : "this is elasticsearch blog"}}
{ "update": { "_id": "4"} }
{ "doc" : {"title" : "this is java, elasticsearch, hadoop blog"}}
{ "update": { "_id": "5"} }
{ "doc" : {"title" : "this is spark blog"}}
2、搜索标题中包含java或elasticsearch的blog
这个，就跟之前的那个term query，不一样了。不是搜索exact value，是进行full text全文检索。match query，是负责进行全文检索的。当然，如果要检索的field，是not_analyzed类型的，那么match query也相当于term query。
GET /waws/article/_search
{
"query": {
"match": {
"title": "java elasticsearch"
}
}
}
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0.5910557,
"hits": [
{
"_index": "waws",
"_type": "article",
"_id": "4",
"_score": 0.5910557,
"_source": {
"articleID": "QQPX-R-3956-#aD8",
"userID": 2,
"hidden": true,
"postDate": "2017-01-02",
"tag": [
"java",
"elasticsearch"
],
"tag_cnt": 2,
"view_cnt": 80,
"title": "this is java, elasticsearch, hadoop blog"
}
},
{
"_index": "waws",
"_type": "article",
"_id": "3",
"_score": 0.2876821,
"_source": {
"articleID": "JODL-X-1937-#pV7",
"userID": 2,
"hidden": false,
"postDate": "2017-01-01",
"tag": [
"hadoop"
],
"tag_cnt": 1,
"view_cnt": 100,
"title": "this is elasticsearch blog"
}
},
{
"_index": "waws",
"_type": "article",
"_id": "1",
"_score": 0.26742277,
"_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"
}
}
]
}
}
3、搜索标题中包含java和elasticsearch的blog 搜索结果精准控制的第一步：灵活使用and关键字，如果你是希望所有的搜索关键字都要匹配的，那么就用and，可以实现单纯match query无法实现的效果
GET /waws/article/_search
{
"query": {
"match": {
"title": {
"query": "java elasticsearch",
"operator": "and"
}
}
}
}
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0.7465237,
"hits": [
{
"_index": "waws",
"_type": "article",
"_id": "4",
"_score": 0.7465237,
"_source": {
"articleID": "QQPX-R-3956-#aD8",
"userID": 2,
"hidden": true,
"postDate": "2017-01-02",
"tag": [
"java",
"elasticsearch"
],
"tag_cnt": 2,
"view_cnt": 80,
"title": "this is java, elasticsearch, hadoop blog"
}
},
{
"_index": "waws",
"_type": "article",
"_id": "1",
"_score": 0.53484553,
"_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"
}
}
]
}
}
4、搜索包含java，elasticsearch，spark，hadoop，4个关键字中，至少3个的blog
控制搜索结果的精准度的第二步：指定一些关键字中，必须至少匹配其中的多少个关键字，才能作为结果返回
GET /waws/article/_search
{
"query": {
"match": {
"title": {
"query": "java elasticsearch spark hadoop",
"minimum_should_match": "75%"
}
}
}
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1.3375794,
"hits": [
{
"_index": "waws",
"_type": "article",
"_id": "4",
"_score": 1.3375794,
"_source": {
"articleID": "QQPX-R-3956-#aD8",
"userID": 2,
"hidden": true,
"postDate": "2017-01-02",
"tag": [
"java",
"elasticsearch"
],
"tag_cnt": 2,
"view_cnt": 80,
"title": "this is java, elasticsearch, hadoop blog"
}
}
]
}
}
5、用bool组合多个搜索条件，来搜索title
GET /waws/article/_search
{
"query": {
"bool": {
"must": { "match": { "title": "java" }},
"must_not": { "match": { "title": "spark" }},
"should": [
{ "match": { "title": "hadoop" }},
{ "match": { "title": "elasticsearch" }}
]
}
}
}
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 1.3375794,
"hits": [
{
"_index": "waws",
"_type": "article",
"_id": "4",
"_score": 1.3375794,
"_source": {
"articleID": "QQPX-R-3956-#aD8",
"userID": 2,
"hidden": true,
"postDate": "2017-01-02",
"tag": [
"java",
"elasticsearch"
],
"tag_cnt": 2,
"view_cnt": 80,
"title": "this is java, elasticsearch, hadoop blog"
}
},
{
"_index": "waws",
"_type": "article",
"_id": "1",
"_score": 0.53484553,
"_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"
}
},
{
"_index": "waws",
"_type": "article",
"_id": "2",
"_score": 0.19856805,
"_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"
}
}
]
}
}
6、bool组合多个搜索条件，如何计算relevance score
must和should搜索对应的分数，加起来，除以must和should的总数
- 排名第一：java，同时包含should中所有的关键字，hadoop，elasticsearch
- 排名第二：java，同时包含should中的elasticsearch
- 排名第三：java，不包含should中的任何关键字
should是可以影响相关度分数的
must是确保说，谁必须有这个关键字，同时会根据这个must的条件去计算出document对这个搜索条件的relevance score
在满足must的基础之上，should中的条件，不匹配也可以，但是如果匹配的更多，那么document的relevance score就会更高
7、搜索java，hadoop，spark，elasticsearch，至少包含其中3个关键字
默认情况下，should是可以不匹配任何一个的，比如上面的搜索中，this is java blog，就不匹配任何一个should条件
但是有个例外的情况，如果没有must的话，那么should中必须至少匹配一个才可以 比如下面的搜索，should中有4个条件，默认情况下，只要满足其中一个条件，就可以匹配作为结果返回
但是可以精准控制，should的4个条件中，至少匹配几个才能作为结果返回
GET /waws/article/_search
{
"query": {
"bool": {
"should": [
{ "match": { "title": "java" }},
{ "match": { "title": "elasticsearch" }},
{ "match": { "title": "hadoop" }},
{ "match": { "title": "spark" }}
],
"minimum_should_match": 3
}
}
}
Elasticsearch高手进阶篇(8)
深度探秘搜索技术_基于term+bool实现的multiword搜索底层原理剖析
1、普通match如何转换为term+should
{
"match": { "title": "java elasticsearch"}
}
使用诸如上面的match query进行多值搜索的时候，es会在底层自动将这个match query转换为bool的语法 bool should，指定多个搜索词，同时使用term query
{
"bool": {
"should": [
{"term": { "title": "java" }},
{"term": { "title": "elasticsearch"}}
]
}
}
2、and match如何转换为term+must
{
"match": {
"title": {
"query": "java elasticsearch",
"operator": "and"
}
}
}
{
"bool": {
"must": [
{ "term": { "title": "java" }},
{ "term": { "title": "elasticsearch" }}
]
}
}
3、minimum_should_match如何转换
{
"match": {
"title": {
"query":"java elasticsearch hadoop spark",
"minimum_should_match": "75%"
}
}
}
{
"bool": {
"should": [
{ "term": { "title": "java" }},
{ "term": { "title": "elasticsearch"}},
{ "term": { "title": "hadoop" }},
{ "term": { "title": "spark" }}
],
"minimum_should_match": 3
}
}
上一讲，为啥要讲解两种实现multi-value搜索的方式呢？实际上，就是给这一讲进行铺垫的。match query --> bool + term
