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ElasticSearch學(xué)習(xí)之多條件組合查詢驗(yàn)證及示例分析

 更新時(shí)間:2023年02月02日 16:01:32   作者:程序員皮卡秋  
這篇文章主要為大家介紹了ElasticSearch 多條件組合查詢驗(yàn)證及示例分析,有需要的朋友可以借鑒參考下,希望能夠有所幫助,祝大家多多進(jìn)步,早日升職加薪

多條件組合查詢

bool

es中使用bool來控制多條件查詢,bool查詢支持以下參數(shù):

  • must:被查詢的數(shù)據(jù)必須滿足當(dāng)前條件
  • mush_not:被查詢的數(shù)據(jù)必須不滿足當(dāng)前條件
  • should:被查詢的數(shù)據(jù)應(yīng)該滿足當(dāng)前條件。should查詢被用于修正查詢結(jié)果的評(píng)分。需要注意的是,如果組合查詢中沒有must,那么被查詢的數(shù)據(jù)至少要匹配一條should。如果有must語句,那么就無須匹配should,should將完全用于修正查詢結(jié)果的評(píng)分
  • filter:被查詢的數(shù)據(jù)必須滿足當(dāng)前條件,但是filter操作不涉及查詢結(jié)果評(píng)分。僅用于條件過濾

下面通過一個(gè)例子來看下如何使用:

GET class_1/_search
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "name": "apple"
        }}
      ],
      "must_not": [
        {"term": {
          "num": {
            "value": "5"
          }
        }}
      ],
      "should": [
        {"match": {
          "name": "k"
        }}
      ],"filter": [
        {"range": {
          "num": {
            "gte": 0,
            "lte": 10
          }
        }}
      ]
    }
  }
}

結(jié)果返回:

{
  "took" : 9,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.752627,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : 0.752627,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : 0.752627,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : 0.7389809,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        }
      }
    ]
  }
}

constant_score

constant_score查詢可以通過boost指定一個(gè)固定的評(píng)分,通常來說,constant_score的作用是代替一個(gè)只有filterbool查詢

下面看具體使用:

GET class_1/_search
{
  "query": {
    "constant_score": {
      "filter": {
        "term": {
          "num": 6
        }
      },
      "boost": 1.2
    }
  }
}

返回:

{
  "took" : 7,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 1.2,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "h2Fg-4UBECmbBdQA6VLg",
        "_score" : 1.2,
        "_source" : {
          "name" : "b",
          "num" : 6
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.2,
        "_source" : {
          "name" : "l",
          "num" : 6
        }
      }
    ]
  }
}

查詢驗(yàn)證 & 分析

驗(yàn)證

es中通過/_validate/query路由來驗(yàn)證查詢條件的正確性, 這里要注意是驗(yàn)證查詢條件是否準(zhǔn)確

示例:

GET class_1/_validate/query?explain
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "name": "apple"
        }}
      ]
    }
  }
}

正常返回:

{
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "failed" : 0
  },
  "valid" : true,
  "explanations" : [
    {
      "index" : "class_1",
      "valid" : true,
      "explanation" : "+name:apple"
    }
  ]
}

name字段改為 name1再查詢:

{
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "failed" : 0
  },
  "valid" : true,
  "explanations" : [
    {
      "index" : "class_1",
      "valid" : true,
      "explanation" : """+MatchNoDocsQuery("unmapped fields [name1]")"""
    }
  ]
}

可以看到報(bào)了異常錯(cuò)誤

分析

es中通過/_validate/query?explain路由來進(jìn)行查詢分析

示例:

GET class_1/_validate/query?explain
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "name": "apple so"
        }}
      ]
    }
  }
}

返回:

{
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "failed" : 0
  },
  "valid" : true,
  "explanations" : [
    {
      "index" : "class_1",
      "valid" : true,
      "explanation" : "+(name:apple name:so)"
    }
  ]
}

可以看到"explanation" : "+(name:apple name:so)",查詢的短語apple so被進(jìn)行了分詞,分成了name:apple, name: so

排序

默認(rèn)排序

在前面的幾個(gè)例子中,我們可以看到它的默認(rèn)排序是按照_score降序,也就是匹配度高的比較靠前,但是_socre的計(jì)算是很占用查詢性能的,這個(gè)不難理解。

當(dāng)我們不需要進(jìn)行_score計(jì)算,可以通過filterconstant_score來進(jìn)行構(gòu)建查詢條件

filter示例:

GET class_1/_search
{
  "query": {
    "bool": {
      "filter": [
        {"term": {
          "num": 1
        }}
      ]
    }
  }
}

返回:

{
  "took" : 5,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.0,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : 0.0,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : 0.0,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : 0.0,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        }
      }
    ]
  }
}

通過查詢結(jié)果我們發(fā)現(xiàn)score都為0.0了,說明沒有進(jìn)行score計(jì)算

constant_score示例:

GET class_1/_search
{
  "query": {
    "constant_score": {
      "filter": {
        "term": {
          "num": 1
        }
      },
      "boost": 1.2
    }
  }
}

返回:

{
  "took" : 3,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 1.2,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : 1.2,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : 1.2,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : 1.2,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        }
      }
    ]
  }
}

可以看到,對(duì)應(yīng)返回的分值,都是使用boost屬性指定的分值

自定義排序

自定義可以用于大部分場(chǎng)景,那么es中怎么進(jìn)行自定義排序呢? es中使用sort參數(shù)來自定義排序順序,默認(rèn)為升序,那么降序怎么操作呢?

  • 升序
{"sort":["num"]}
  • 降序, desc代表降序
{"sort":[{"num":{"order":"desc"}}]} 

tips

  • es中使用doc value列式存儲(chǔ)來實(shí)現(xiàn)字段的排序功能
  • text字段默認(rèn)不創(chuàng)建doc value,因此無法針對(duì)text字段進(jìn)行排序
  • 可以通過設(shè)置text字段屬性fielddata=true來開啟對(duì)text字段的排序功能,但是不建議開啟,對(duì)text字段排序及其消耗查詢性能且不符合需求

單字段排序

GET class_1/_search
{
    "sort": [
        "num"
    ]
}

返回:

{
  "took" : 6,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 11,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : null,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        },
        "sort" : [
          1
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : null,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        },
        "sort" : [
          1
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : null,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        },
        "sort" : [
          1
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "h2Fg-4UBECmbBdQA6VLg",
        "_score" : null,
        "_source" : {
          "name" : "b",
          "num" : 6
        },
        "sort" : [
          6
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : null,
        "_source" : {
          "name" : "l",
          "num" : 6
        },
        "sort" : [
          6
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : null,
        "_source" : {
          "num" : 9,
          "name" : "e",
          "age" : 9,
          "desc" : [
            "hhhh"
          ]
        },
        "sort" : [
          9
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "4",
        "_score" : null,
        "_source" : {
          "name" : "f",
          "age" : 10,
          "num" : 10
        },
        "sort" : [
          10
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "RWlfBIUBDuA8yW5cu9wu",
        "_score" : null,
        "_source" : {
          "name" : "一年級(jí)",
          "num" : 20
        },
        "sort" : [
          20
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "iGFt-4UBECmbBdQAnVJe",
        "_score" : null,
        "_source" : {
          "name" : "g",
          "age" : 8
        },
        "sort" : [
          9223372036854775807
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "iWFt-4UBECmbBdQAnVJg",
        "_score" : null,
        "_source" : {
          "name" : "h",
          "age" : 9
        },
        "sort" : [
          9223372036854775807
        ]
      }
    ]
  }
}

可以看到是按照num默認(rèn)升序排序

再看下降序:

GET class_1/_search
{
    "sort": [
        {"num": {"order":"desc"}}
    ]
}

返回:

{
  "took" : 15,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 11,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "RWlfBIUBDuA8yW5cu9wu",
        "_score" : null,
        "_source" : {
          "name" : "一年級(jí)",
          "num" : 20
        },
        "sort" : [
          20
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "4",
        "_score" : null,
        "_source" : {
          "name" : "f",
          "age" : 10,
          "num" : 10
        },
        "sort" : [
          10
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : null,
        "_source" : {
          "num" : 9,
          "name" : "e",
          "age" : 9,
          "desc" : [
            "hhhh"
          ]
        },
        "sort" : [
          9
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "h2Fg-4UBECmbBdQA6VLg",
        "_score" : null,
        "_source" : {
          "name" : "b",
          "num" : 6
        },
        "sort" : [
          6
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : null,
        "_source" : {
          "name" : "l",
          "num" : 6
        },
        "sort" : [
          6
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : null,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        },
        "sort" : [
          1
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : null,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        },
        "sort" : [
          1
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : null,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        },
        "sort" : [
          1
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "iGFt-4UBECmbBdQAnVJe",
        "_score" : null,
        "_source" : {
          "name" : "g",
          "age" : 8
        },
        "sort" : [
          -9223372036854775808
        ]
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "iWFt-4UBECmbBdQAnVJg",
        "_score" : null,
        "_source" : {
          "name" : "h",
          "age" : 9
        },
        "sort" : [
          -9223372036854775808
        ]
      }
    ]
  }
}

這下就降序排序了

多字段

GET class_1/_search
{
    "sort": [
        "num", "age"
    ]
}

scroll分頁

還記得之前給大家講的from+size的分頁方式嗎,es中默認(rèn)允許from+size的分頁的最大數(shù)據(jù)量為10000。當(dāng)我們想要批量獲取更大的數(shù)據(jù)量時(shí),使用from+size就會(huì)十分的耗費(fèi)性能。

然而大部分應(yīng)用場(chǎng)景下的數(shù)據(jù)量是極其龐大的,比如你要查詢某些系統(tǒng)日志數(shù)據(jù)。es中可以使用/scorll路由來進(jìn)行滾動(dòng)分頁查詢,它類似于在查詢初始時(shí)間點(diǎn)創(chuàng)建了一個(gè)當(dāng)前服務(wù)集群的數(shù)據(jù)快照(包含每一個(gè)分片),并保留它一段時(shí)間。在時(shí)間超過了設(shè)置的過期時(shí)間以后,快照將在es空閑時(shí)被刪除。

需要注意的是,因?yàn)槭沁M(jìn)行快照查詢,因此在快照創(chuàng)建后數(shù)據(jù)的變更在本次的滾動(dòng)查詢中,不可見

初始化快照 & 快照保存10分鐘

查詢示例:

GET class_1/_search?scroll=10m
{
"query": {
 "match_phrase": {
   "name": "apple"
 }
},
"size": 2
}

返回:

{
  "_scroll_id" : "DnF1ZXJ5VGhlbkZldGNoAwAAAAAAAAXoFjEwWkdOMkxLUTVPZEMzM01ZdHhPc1EAAAAAAAACABZjUy1CemQwQVFfU3BUeGs2OGk0R1Z3AAAAAAAAAgEWY1MtQnpkMEFRX1NwVHhrNjhpNEdWdw==",
  "took" : 6,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.752627,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : 0.752627,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : 0.752627,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        }
      }
    ]
  }
}

如圖,當(dāng)前共返回2條數(shù)據(jù),并且返回了一個(gè)快照ID,后續(xù)可以根據(jù)快照ID進(jìn)行滾動(dòng)查詢:

根據(jù)快照ID滾動(dòng)查詢

GET /_search/scroll
{
 "scroll": "10m", 
 "scroll_id" : "DnF1ZXJ5VGhlbkZldGNoAwAAAAAAAAXoFjEwWkdOMkxLUTVPZEMzM01ZdHhPc1EAAAAAAAACABZjUy1CemQwQVFfU3BUeGs2OGk0R1Z3AAAAAAAAAgEWY1MtQnpkMEFRX1NwVHhrNjhpNEdWdw=="
}

返回:

{
  "_scroll_id" : "DnF1ZXJ5VGhlbkZldGNoAwAAAAAAAAXoFjEwWkdOMkxLUTVPZEMzM01ZdHhPc1EAAAAAAAACABZjUy1CemQwQVFfU3BUeGs2OGk0R1Z3AAAAAAAAAgEWY1MtQnpkMEFRX1NwVHhrNjhpNEdWdw==",
  "took" : 6,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.752627,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : 0.7389809,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        }
      }
    ]
  }
}

在滾動(dòng)一次:

{
  "_scroll_id" : "DnF1ZXJ5VGhlbkZldGNoAwAAAAAAAAXoFjEwWkdOMkxLUTVPZEMzM01ZdHhPc1EAAAAAAAACABZjUy1CemQwQVFfU3BUeGs2OGk0R1Z3AAAAAAAAAgEWY1MtQnpkMEFRX1NwVHhrNjhpNEdWdw==",
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.752627,
    "hits" : [ ]
  }
}

有的小伙伴可能不知道怎么滾動(dòng)的,因?yàn)楹罄m(xù)滾動(dòng)都是同一個(gè)scroll_id,其實(shí)通過結(jié)果,我們不難發(fā)現(xiàn):

  • 首先創(chuàng)建了一個(gè)10分鐘的快照,規(guī)定了每次返回的數(shù)據(jù)量為2條,并且初始化的時(shí)候,返回了2條
  • 通過scroll_id進(jìn)行滾動(dòng)操作,返回了1條數(shù)據(jù),原因是快照的數(shù)據(jù)量總共只有3條,初始化的時(shí)候返回了2條,所以現(xiàn)在只有1條
  • 再次滾動(dòng)的時(shí)候,發(fā)現(xiàn)返回了空,因?yàn)閿?shù)據(jù)已經(jīng)被查完了

以上就是ElasticSearch 多條件組合查詢驗(yàn)證及示例分析的詳細(xì)內(nèi)容,更多關(guān)于ElasticSearch 多條件組合查詢的資料請(qǐng)關(guān)注腳本之家其它相關(guān)文章!

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