数据准备
POST /blog/_doc/_bulk
{"index":{"_id":1}}
{"title":"安徽合肥"}
{"index":{"_id":2}}
{"title":"安徽宣城"}
{"index":{"_id":3}}
{"title":"江苏南京"}
{"index":{"_id":4}}
{"title":"山东肥城"}
{"index":{"_id":5}}
{"title":"陕西西安"}
term
team 为精确查询
会将需要查询的值完整的去到索引中进行匹配查找
案例1
GET blog/_doc/_search
{"query":{"term":{"title":"安"}}}
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0.6931472,
"hits": [
{
"_index": "blog",
"_type": "_doc",
"_id": "2",
"_score": 0.6931472,
"_source": {
"title": "安徽宣城"
}
},
{
"_index": "blog",
"_type": "_doc",
"_id": "5",
"_score": 0.2876821,
"_source": {
"title": "陕西西安"
}
},
{
"_index": "blog",
"_type": "_doc",
"_id": "1",
"_score": 0.2876821,
"_source": {
"title": "安徽合肥"
}
}
]
}
}
因为 安徽宣城，陕西西安，安徽合肥 这些文本在进行文本分析时，都有安出现，所以根据倒排索引能查到这三条数据；
POST blog/_analyze
{
"field": "title",
"text": "安徽合肥"
}
{
"tokens": [
{
"token": "安",
"start_offset": 0,
"end_offset": 1,
"type": "<IDEOGRAPHIC>",
"position": 0
},
{
"token": "徽",
"start_offset": 1,
"end_offset": 2,
"type": "<IDEOGRAPHIC>",
"position": 1
},
{
"token": "合",
"start_offset": 2,
"end_offset": 3,
"type": "<IDEOGRAPHIC>",
"position": 2
},
{
"token": "肥",
"start_offset": 3,
"end_offset": 4,
"type": "<IDEOGRAPHIC>",
"position": 3
}
]
}
案例2
GET blog/_doc/_search
{"query":{"term":{"title":"安徽合肥"}}}
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 0,
"max_score": null,
"hits": []
}
}
查看结果会发现一条都没有查询到，有点反常识；但如果结合案例1大概就能明白，文本 安徽合肥在分词创建倒排索引时，并没有保留一个完整的文本作为索引，而是四个单独的字作为索引；
而 team 为精确查询，所以根据安徽合肥到倒排索引中并不会搜索到数据；
知识拓展 如果结合elasticsearch系统学习笔记5-中文分词器中的知识， 在创建 blog索引 时将 title 字段指定为
ik_max_word
GET /_analyze
{
"text": "安徽合肥",
"analyzer": "ik_max_word"
}
{
"tokens": [
{
"token": "安徽",
"start_offset": 0,
"end_offset": 2,
"type": "CN_WORD",
"position": 0
},
{
"token": "合肥",
"start_offset": 2,
"end_offset": 4,
"type": "CN_WORD",
"position": 1
}
]
}
文本 `安徽合肥`在分词创建倒排索引时，将会被分词成 "安徽" 和 "合肥"
案例3
GET blog/_doc/_search
{"query":{"term":{"title.keyword":"安徽合肥"}}}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 0.2876821,
"hits": [
{
"_index": "blog",
"_type": "_doc",
"_id": "1",
"_score": 0.2876821,
"_source": {
"title": "安徽合肥"
}
}
]
}
}
在字段名后加上个 .keyword 就能查询到，这是因为创建索引 blog 时字段 title 有一个子属性就是 keyword ；
GET /blog/_mapping
{
"blog": {
"mappings": {
"_doc": {
"properties": {
"title": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
}
}
}
}
}
match
https://www.elastic.co/guide/en/elasticsearch/reference/6.3/query-dsl-match-query.html
案例1
GET blog/_doc/_search
{"query":{"match":{"title":"安"}}}
{
"took": 12,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 4,
"max_score": 1.3862944,
"hits": [
{
"_index": "blog",
"_type": "_doc",
"_id": "2",
"_score": 1.3862944,
"_source": {
"title": "安徽宣城"
}
},
{
"_index": "blog",
"_type": "_doc",
"_id": "1",
"_score": 1.1507283,
"_source": {
"title": "安徽合肥"
}
},
{
"_index": "blog",
"_type": "_doc",
"_id": "4",
"_score": 0.6931472,
"_source": {
"title": "山东肥城"
}
},
{
"_index": "blog",
"_type": "_doc",
"_id": "5",
"_score": 0.2876821,
"_source": {
"title": "陕西西安"
}
}
]
}
}
如果根据单个字或词来看，term 和 match 并没有什么区别
案例2
GET blog/_doc/_search
{"query":{"match":{"title":"安徽合肥"}}}
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 4,
"max_score": 1.3862944,
"hits": [
{
"_index": "blog",
"_type": "_doc",
"_id": "2",
"_score": 1.3862944,
"_source": {
"title": "安徽宣城"
}
},
{
"_index": "blog",
"_type": "_doc",
"_id": "1",
"_score": 1.1507283,
"_source": {
"title": "安徽合肥"
}
},
{
"_index": "blog",
"_type": "_doc",
"_id": "4",
"_score": 0.6931472,
"_source": {
"title": "山东肥城"
}
},
{
"_index": "blog",
"_type": "_doc",
"_id": "5",
"_score": 0.2876821,
"_source": {
"title": "陕西西安"
}
}
]
}
}
如果是多个词或字的查询，就与 term 不太一样了，这是因为 match 在查询之前会将 安徽合肥 进行分词 ，按照安,徽,合,肥分别查询并将结果汇总；
不信你可以使用下面的语句再查询一遍，结果还是一样的
GET blog/_doc/_search
{"query":{"match":{"title":"安肥合徽"}}}
作用类似于
GET blog/_doc/_search
{
"query": {
"terms": {
"title": ["安","徽","合","肥"]
}
}
}
或者
GET blog/_doc/_search
{
"query": {
"bool": {
"should": [
{"match":{"title":"安"}},
{"match":{"title":"徽"}},
{"match":{"title":"合"}},
{"match":{"title":"肥"}}
]
}
}
}
案例3
GET blog/_doc/_search
{
"query": {
"match": {
"title": {
"query": "安徽合肥",
"operator": "and"
}
}
}
}
{
"took": 37,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1.1507283,
"hits": [
{
"_index": "blog",
"_type": "_doc",
"_id": "1",
"_score": 1.1507283,
"_source": {
"title": "安徽合肥"
}
}
]
}
}
增加 operator 查询条件，代表一个逻辑语句，这里表示需要同时满足安,徽,合,肥这四个条件才可以；
其实只要一个文本里包含这四个字的文档，都会被检索出来；
类似于：
GET blog/_doc/_search
{
"query": {
"bool": {
"must": [
{"match":{"title":"安"}},
{"match":{"title":"徽"}},
{"match":{"title":"合"}},
{"match":{"title":"肥"}}
]
}
}
}
案例4
GET blog/_doc/_search
{"query":{"match_phrase":{"title":"安徽合肥"}}}
{
"took": 16,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1.1507283,
"hits": [
{
"_index": "blog",
"_type": "_doc",
"_id": "1",
"_score": 1.1507283,
"_source": {
"title": "安徽合肥"
}
}
]
}
}
match_phrase 短语匹配
用于全文搜索，当你希望寻找邻近的单词时，match_phrase 查询可以满足要求；
也可以通过配置 slop 指定 match_phrase 查询词条能够相隔多远时仍然将文档视为匹配；（0 是默认值）
GET blog/_doc/_search
{
"query": {
"match_phrase": {
"title": {
"query": "安徽合肥",
"slop": 0
}
}
}
}
