elasticsearch-搜索-基本搜索(四)

多索引多type搜索

分页搜索

每页5条查询一到3页数据

第一页:http://127.0.0.1:9200/blogs2/product/_search?size=5&from=0

第二页:http://127.0.0.1:9200/blogs2/product/_search?size=5&from=5

第三页:http://127.0.0.1:9200/blogs2/product/_search?size=5&from=10

size参数为每页显示数量 from为跳过前面数量

搜索文档的一部分

或者通过指定排除属性和包含属性支持匹配

http://localhost:9200/twitter/tweet/1?_source_include=*.id&_source_exclude=entities

搜索多个索引（type）文档

参数

{
    "docs":[{
        "_index":"blogs",
        "_type":"product",
        "_id":"1"
    },{
            "_index":"blogs2",
        "_type":"product",
        "_id":"2"
    }]
}

结果

{
    "docs": [
        {
            "_index": "blogs",
            "_type": "product",
            "_id": "1",
            "_version": 13,
            "_seq_no": 10,
            "_primary_term": 1,
            "found": true,
            "_source": {
                "productName": "测试修改",
                "price": 11,
                "remark": "不错的床垫",
                "tags": [
                    "家具",
                    "床垫",
                    "棉花",
                    null
                ],
                "videw": 1
            }
        },
        {
            "_index": "blogs2",
            "_type": "product",
            "_id": "2",
            "_version": 1,
            "_seq_no": 0,
            "_primary_term": 1,
            "found": true,
            "_source": {
                "productName": "法瑞思 天然椰棕床垫棕垫硬床垫定做 薄乳胶棕榈榻榻米床垫定制折叠1.2/1.5/1.8",
                "price": 10,
                "remark": "不错的床垫",
                "tags": [
                    "家具",
                    "床垫",
                    "棉花"
                ]
            }
        }
    ]
}

如果index相同type不同

简易搜索

查询产品名字包含沙发同时品牌id为1的产品信息

or搜索？

文档是and搜索我测试时or搜索

http://127.0.0.1:9200/blogs2/product/_search?q=productName:大幅度 +price:10 如果一个字段多只查询 http://127.0.0.1:9200/blogs2/product/_search?q=productName:(大幅度床垫) +price:10

所有字段中查询

查询所有字段里面包含床垫的文档

http://127.0.0.1:9200/blogs2/product/_search?q=测试

ES会将文档里面的所有值都拼接成一个串来查找

结构化查询DSL

term(=)过滤

主要用于精确匹配比如年龄 bool

{
    "query":{
        "term":{
        "price":12
        }
    }
}

terms(in)过滤

跟term相同 terms支持多值搜索下面会搜索出单价为12和13的搜索出来

{
    "query":{
        "terms":{
        "price":[12,13]
        }
    }
}

range(between)过滤

{
    "query": {
        "range": {
            "price": {
                "gt": 10
            }
        }
    }
}

将会查出价格大于10的 gt大于lt小于 gte大于等于 lte小于等于

大于等于小余等于

{
    "query": {
        "range": {
            "price": {
                "gt": 10,
                 "lt":13
            }
        }
    }
}

exist

查询不存在指定字段的所有文档

{
    "query": {
        "missing": {
            "field":"price"
        }
    }
}

字段不存在或为空判断

{
    "query": {
        "bool": {
            "must_not": {
                "exists": {
                    "field": "price"
                }
            }
        }
    }
}

存在指定字段查询

{
  "query": {
    "bool": {
      "filter": {
        "exists": {
          "field": "productSortItemIds"
        }
      }
    }
  }
}

bool过滤

合并多个查询条件的bool值

must:多个条件完全匹配相当于and

must_not 多个条件取想法相当于<>

should: 至少有一个条件匹配相当于or

如下面例子

{
    "query": {
        "bool": {
            "must":[
                {"term":{"price":10}},
                {"term":{"orgId":1}}
            ],
            "numst_not":{
                "term":{"id":1}
            },
            "should":[
                {"term":{"id":10}},
                {"term":{"id":20}}
            ]
        }
    }
}

(price=10 and orgId=1) and (id<>1) and (id=10 or id=20)

match_all

空查询

{
    "query": {
        "match_all":{}
    }
}

match(like)

在搜索确定值类型字段将会按照完全匹配。如果是full text则是采用分词

{
    "query": {
        "match":{"price":10}
    }
}

mult_match( like and)

与match相同只是允许同时搜索多个字段 operator 是默认搜索字段会分词，只是区分分词匹配是and全部匹配或者or部分匹配

{
  "query": {
    "multi_match": {
      "query": "不错的",
      "fields": [
         "productName","remark"
      ],
      "operator": "AND"//OR AND
    }
  }
}

filter

filter将不进行_score打分性能会高一点

{
    "query": {
        "bool": {
            "must": {
                "match": {
                    "productName": "床垫"
                }
            },
            "filter": {
                "match": {
                    "remark": "床垫"
                }

            }
        }
    }
}

is null查询

需要在创建mapping的时候设置字段的null_value 然后match搜索就搜索设置的value就行了

验证查询

验证一个查询是否有效

查询搜索分词索引情况

http://127.0.0.1:9200/blogs2/product/_validate/query?explain

脚本字段

可以通过脚本计算结果但是不会返回其他字段到时有需求可以研究一下

#localhost:9200/test_3/doc/_search
{
    "script_fields":{
        "new_filed":{
            "script":{
                "lang":"painless",
                "source":"doc['isActived'].value+1"
            }
        }
    }
}

响应

{
    "took": 4,
    "timed_out": false,
    "_shards": {
        "total": 5,
        "successful": 5,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": 62342,
        "max_score": 1.0,
        "hits": [
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "843_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "250_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "1040_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "984_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "284_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "486_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "414_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "1190_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "553_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            },
            {
                "_index": "test_3",
                "_type": "doc",
                "_id": "867_CB407",
                "_score": 1.0,
                "fields": {
                    "new_filed": [
                        2
                    ]
                }
            }
        ]
    }
}

View Code

查询权重分计算

get http://127.0.0.1:9200/index/type/id/_explain

body

{
    "query":{
        "match":{
            "productName":"jw"
        }
    }
}

返回结果

{
    "_index": "test",
    "_type": "doc",
    "_id": "560_406",
    "matched": true,
    "explanation": {
        "value": 5.3691883,
        "description": "sum of:",
        "details": [
            {
                "value": 2.6373672,
                "description": "weight(Synonym(productName:j productName:jw) in 0) [PerFieldSimilarity], result of:",
                "details": [
                    {
                        "value": 2.6373672,
                        "description": "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
                        "details": [
                            {
                                "value": 2.0502589,
                                "description": "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
                                "details": [
                                    {
                                        "value": 56,
                                        "description": "docFreq",
                                        "details": []
                                    },
                                    {
                                        "value": 438,
                                        "description": "docCount",
                                        "details": []
                                    }
                                ]
                            },
                            {
                                "value": 1.2863581,
                                "description": "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
                                "details": [
                                    {
                                        "value": 1,
                                        "description": "termFreq=1.0",
                                        "details": []
                                    },
                                    {
                                        "value": 1.2,
                                        "description": "parameter k1",
                                        "details": []
                                    },
                                    {
                                        "value": 0.75,
                                        "description": "parameter b",
                                        "details": []
                                    },
                                    {
                                        "value": 32.90639,
                                        "description": "avgFieldLength",
                                        "details": []
                                    },
                                    {
                                        "value": 15,
                                        "description": "fieldLength",
                                        "details": []
                                    }
                                ]
                            }
                        ]
                    }
                ]
            },
            {
                "value": 2.731821,
                "description": "weight(productName:w in 0) [PerFieldSimilarity], result of:",
                "details": [
                    {
                        "value": 2.731821,
                        "description": "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
                        "details": [
                            {
                                "value": 2.1236863,
                                "description": "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
                                "details": [
                                    {
                                        "value": 52,
                                        "description": "docFreq",
                                        "details": []
                                    },
                                    {
                                        "value": 438,
                                        "description": "docCount",
                                        "details": []
                                    }
                                ]
                            },
                            {
                                "value": 1.2863581,
                                "description": "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
                                "details": [
                                    {
                                        "value": 1,
                                        "description": "termFreq=1.0",
                                        "details": []
                                    },
                                    {
                                        "value": 1.2,
                                        "description": "parameter k1",
                                        "details": []
                                    },
                                    {
                                        "value": 0.75,
                                        "description": "parameter b",
                                        "details": []
                                    },
                                    {
                                        "value": 32.90639,
                                        "description": "avgFieldLength",
                                        "details": []
                                    },
                                    {
                                        "value": 15,
                                        "description": "fieldLength",
                                        "details": []
                                    }
                                ]
                            }
                        ]
                    }
                ]
            }
        ]
    }
}