search api的基本语法
语法概要：
GET /_search
{}
GET /index1,index2/type1,type2/_search
{}
GET /_search { "from": 0, "size": 10 }
http协议中get是否可以带上request body？
HTTP协议，一般不允许get请求带上request body，但是因为get更加适合描述查询数据的操作，因此还是这么用了。
很多浏览器，或者是服务器，也都支持GET+request body模式
如果遇到不支持的场景，也可以用POST /_search
GET /_search?from=0&size=10 POST /_search { "from":0, "size":10 }
query DSL
一个例子让你明白什么是query DSL
GET /_search { "query": { "match_all": {} } }
Query DSL的基本语法
GET /{index}/_search/{type}
{
"各种条件"
}
示例：
GET /test_index/test_type/_search { "query": { "match": { "test_field": "test" } } } { "took": 1, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 3, "max_score": 0.843298, "hits": [ { "_index": "test_index", "_type": "test_type", "_id": "6", "_score": 0.843298, "_source": { "test_field": "test test" } }, { "_index": "test_index", "_type": "test_type", "_id": "8", "_score": 0.43445712, "_source": { "test_field": "test client 2" } }, { "_index": "test_index", "_type": "test_type", "_id": "7", "_score": 0.25316024, "_source": { "test_field": "test client 1" } } ] } }
组合多个搜索条件
搜索需求：title必须包含elasticsearch，content可以包含elasticsearch也可以不包含，author_id必须不为111
构造数据：
PUT /website/article/1 { "title":"my elasticsearch article", "content":"es is very bad", "author_id":110 } PUT /website/article/2 { "title":"my hadoop article", "content":"hadoop is very bad", "author_id":111 } PUT /website/article/3 { "title":"my hadoop article", "content":"hadoop is very good", "author_id":111 }
组合查询：
GET /website/article/_search { "query": { "bool": { "must": [ { "match": { "title": "elasticsearch" } } ], "should": [ { "match": { "content": "elasticsearch" } } ], "must_not": [ { "match": { "author_id": 111 } } ] } } }
查询结果：
{ "took": 7, "timed_out": false, "_shards": { "total": 5, "successful": 5, "failed": 0 }, "hits": { "total": 1, "max_score": 0.25316024, "hits": [ { "_index": "website", "_type": "article", "_id": "1", "_score": 0.25316024, "_source": { "title": "my elasticsearch article", "content": "es is very bad", "author_id": 110 } } ] } }
filter与query
初始化数据：
PUT /company/employee/2 { "address": { "country": "china", "province": "jiangsu", "city": "nanjing" }, "name": "tom", "age": 30, "join_date": "2016-01-01" } PUT /company/employee/3 { "address": { "country": "china", "province": "shanxi", "city": "xian" }, "name": "marry", "age": 35, "join_date": "2015-01-01" }
搜索请求：年龄必须大于等于30，同时join_date必须是2016-01-01
GET /company/employee/_search { "query": { "bool": { "must": [ { "match": { "join_date": "2016-01-01" } } ], "filter": { "range": { "age": { "gte": 30 } } } } } }
filter与query对比大揭秘
- filter，仅仅只是按照搜索条件过滤出需要的数据而已，不计算任何相关度分数，对相关度没有任何影响
- query，会去计算每个document相对于搜索条件的相关度，并按照相关度进行排序
一般来说，如果你是在进行搜索，需要将最匹配搜索条件的数据先返回，那么用query；如果你只是要根据一些条件筛选出一部分数据，不关注其排序，那么用filter
除非是你的这些搜索条件，你希望越符合这些搜索条件的document越排在前面返回，那么这些搜索条件要放在query中；如果你不希望一些搜索条件来影响你的document排序，那么就放在filter中即可
filter与query性能
- filter，不需要计算相关度分数，不需要按照相关度分数进行排序，同时还有内置的自动cache最常使用filter的数据
- query，相反，要计算相关度分数，按照分数进行排序，而且无法cache结果
Elasticsearch 实战各种query搜索
各种query搜索语法
-
match_all
GET /_search { "query": { "match_all": {} } }
- match
GET /{index}/_search { "query": { "match": { "FIELD": "TEXT" } } } -
multi match
GET /{index}/_search { "query": { "multi_match": { "query": "", "fields": [] } } }示例
View CodeGET /test_index/test_type/_search { "query": { "multi_match": { "query": "test", "fields": ["test_field", "test_field1"] } } }
- range query
GET /{index}/_search { "query": { "range": { "FIELD": { "gte": 10, "lte": 20 } } } }示例
View CodeGET /company/employee/_search { "query": { "range": { "age": { "gte": 30 } } } }
- term query(与match相比不分词)
GET /{index}/_search { "query": { "term": { "FIELD": { "value": "VALUE" } } } }示例
View CodeGET /test_index/test_type/_search { "query": { "term": { "test_field": "test hello" } } }
-
terms query
GET /{index}/_search { "query": { "terms": { "FIELD": [ "VALUE1", "VALUE2" ] } } }示例
View CodeGET /_search { "query": { "terms": { "tag": [ "search", "full_text", "nosql" ] }} }
- exist query
GET /{index}/_search { "query": { "exists": { "field": "" } } }
多搜索条件组合查询
- bool: must, must_not, should, filter
每个子查询都会计算一个document针对它的相关度分数，然后bool综合所有分数，合并为一个分数，当然filter是不会计算分数的。
GET /company/employee/_search { "query": { "constant_score": { "filter": { "range": { "age": { "gte": 30 } } } } } }
定位不合法的搜索
一般用在那种特别复杂庞大的搜索下，比如你一下子写了上百行的搜索，这个时候可以先用validate api去验证一下，搜索是否合法
GET /test_index/test_type/_validate/query?explain { "query": { "math": { "test_field": "test" } } } { "valid": false, "error": "org.elasticsearch.common.ParsingException: no [query] registered for [math]" }
正常数据
GET /test_index/test_type/_validate/query?explain { "query":{ "match":{ "test_field":"test" } } } { "valid": true, "_shards": { "total": 1, "successful": 1, "failed": 0 }, "explanations": [ { "index": "test_index", "valid": true, "explanation": "+test_field:test #(#_type:test_type)" } ] }
定制搜索结果的排序规则
默认情况下，返回的document是按照_score降序排列的。如果我们想自己定义排序规则怎么办，此时只需要使用sort即可
语法：
# 主要语法 "sort": [ { "FIELD": { "order": "desc" } } ] # 整体位置 GET /{index}/_search { "query": { "constant_score": { "filter": { "exists": { "field": "" } }, "boost": 1.2 } }, "sort": [ { "FIELD": { "order": "desc" } } ] }
示例：
GET company/employee/_search { "query": { "constant_score": { "filter": { "range": { "age": { "gte": 30 } } } } }, "sort": [ { "join_date": { "order": "asc" } } ] }
将一个field索引两次来解决字符串排序问题
如果某个字段的类型是text，在创建索引的时候，针对每个document，对应的这个text字段都会对内容进行分词。由于ES不允许对已经存在的field的类型进行修改，就会导致该字段一直都是会被分词，那么如果之后有需求想对该字段排序，就不行了。具体看下面展示的示例。
# 删除原来的删除索引 DELETE /website # 手动建立索引 PUT /website { "mappings": { "article": { "properties": { "title":{ "type": "text", "fields": { "raw":{ "type": "string", "index": "not_analyzed" } }, "fielddata": true }, "content":{ "type": "text" }, "post_date":{ "type": "date" }, "author_id":{ "type": "long" } } } } }
插入模拟数据
PUT /website/article/1 { "title": "second article", "content": "this is my second article", "post_date": "2017-01-01", "author_id": 110 } PUT /website/article/2 { "title": "first article", "content": "this is my first article", "post_date": "2017-02-01", "author_id": 110 } PUT /website/article/3 { "title": "third article", "content": "this is my third article", "post_date": "2017-03-01", "author_id": 110 }
按照不分词排序
GET /website/article/_search { "query": { "match_all": {} }, "sort": [ { "title.raw": { "order": "desc" } } ] }