1、简介

Elastic 官方网站
Elastic 中文社区
Elasticsearch: 权威指南

2、使用

2.1、创建索引

image.png

  1. {
  2.   "aliases": {
  3.     "customer_remind_alias_sit": {},
  4.     "customer_remind_alias_sst": {},
  5.     "customer_remind_alias_test": {}
  6.   },
  7.   "mappings": {
  8.     "properties": {
  9.       "remindRuleId": {
  10.         "type": "keyword"
  11.       },
  12.       "remindDate": {
  13.         "type": "date",
  14.         "ignore_malformed": true,
  15.         "format": "yyyy-MM-dd"
  16.       },
  17.       "carIdOwnOrg": {
  18.         "type": "keyword"
  19.       },
  20.       "wechatFollower": {
  21.         "type": "keyword"
  22.       },
  23.       "wechatSendState": {
  24.         "type": "keyword"
  25.       },
  26.       "wechatSendDate": {
  27.         "type": "date",
  28.         "ignore_malformed": true,
  29.         "format": "yyyy-MM-dd"
  30.       },
  31.       "phoneSendState": {
  32.         "type": "keyword"
  33.       },
  34.       "phoneSendDate": {
  35.         "type": "date",
  36.         "ignore_malformed": true,
  37.         "format": "yyyy-MM-dd"
  38.       },
  39.       "smsSendState": {
  40.         "type": "keyword"
  41.       },
  42.       "smsSendDate": {
  43.         "type": "date",
  44.         "ignore_malformed": true,
  45.         "format": "yyyy-MM-dd"
  46.       },
  47.       "couponSendState": {
  48.         "type": "keyword"
  49.       },
  50.       "picSendState": {
  51.         "type": "keyword"
  52.       },
  53.       "operatorId": {
  54.         "type": "keyword"
  55.       },
  56.       "state": {
  57.         "type": "keyword"
  58.       },
  59.       "isDeleted": {
  60.         "type": "keyword"
  61.       },
  62.       "operatorProcessState": {
  63.         "type": "keyword"
  64.       },
  65.       "consumeAgainState": {
  66.         "type": "keyword"
  67.       },
  68.       "consumeAgainDate": {
  69.         "type": "date",
  70.         "ignore_malformed": true,
  71.         "format": "yyyy-MM-dd"
  72.       },
  73.       "finishTime": {
  74.         "type": "date",
  75.         "ignore_malformed": true,
  76.         "format": "yyyy-MM-dd"
  77.       },
  78.       "customerName": {
  79.         "type": "text",
  80.         "fields": {
  81.           "raw": {
  82.             "type": "keyword"
  83.           }
  84.         },
  85.         "analyzer": "ngram_10_analyzer"
  86.       },
  87.       "customerCellPhone": {
  88.         "type": "text",
  89.         "analyzer": "ngram_11_analyzer"
  90.       },
  91.       "fullCarNo": {
  92.         "type": "text",
  93.         "fields": {
  94.           "raw": {
  95.             "type": "keyword"
  96.           }
  97.         },
  98.         "analyzer": "ngram_8_analyzer"
  99.       },
  100.       "remindType": {
  101.         "type": "keyword"
  102.       },
  103.       "idOwnOrg": {
  104.         "type": "keyword"
  105.       },
  106.       "creationtime": {
  107.         "type": "date",
  108.         "ignore_malformed": true,
  109.         "format": "yyyy-MM-dd"
  110.       },
  111.       "customerId": {
  112.         "type": "keyword"
  113.       },
  114.       "carId": {
  115.         "type": "keyword"
  116.       },
  117.       "groupId": {
  118.         "type": "keyword"
  119.       },
  120.       "lastServiceDate": {
  121.         "type": "date",
  122.         "ignore_malformed": true,
  123.         "format": "yyyy-MM-dd"
  124.       },
  125.       "lastServiceOrg": {
  126.         "type": "keyword"
  127.       },
  128.       "operatorSendState": {
  129.         "type": "keyword"
  130.       },
  131.       "pkId": {
  132.         "type": "keyword"
  133.       },
  134.       "sourceType": {
  135.             "type": "keyword"
  136.         },
  137.         "lastInsuranceCompanyId ": {
  138.             "type": "keyword"
  139.         },
  140.         "lastInsuranceOrgId ": {
  141.             "type": "keyword"
  142.         },
  143.         "car_exclusive_consultants_id": {
  144.             "type": "keyword"
  145.         }
  146.     }
  147.   },
  148.   "settings": {
  149.     "index": {
  150.       "max_ngram_diff": "19",
  151.       "analysis": {
  152.         "analyzer": {
  153.           "ngram_10_analyzer": {
  154.             "tokenizer": "ngram_10_tokenizer"
  155.           },
  156.           "ngram_11_analyzer": {
  157.             "tokenizer": "ngram_11_tokenizer"
  158.           },
  159.           "ngram_8_analyzer": {
  160.             "tokenizer": "ngram_8_tokenizer"
  161.           }
  162.         },
  163.         "tokenizer": {
  164.           "ngram_10_tokenizer": {
  165.             "type": "ngram",
  166.             "min_gram": "1",
  167.             "max_gram": "20"
  168.           },
  169.           "ngram_11_tokenizer": {
  170.             "type": "ngram",
  171.             "min_gram": "1",
  172.             "max_gram": "11"
  173.           },
  174.           "ngram_8_tokenizer": {
  175.             "type": "ngram",
  176.             "min_gram": "1",
  177.             "max_gram": "8"
  178.           }
  179.         }
  180.       }
  181.     }
  182.   }
  183. }

2.2、状态查询

2.2.1、集群的健康状态

  1. GET _cat/health

2.2.2、节点状态

  1. GET _cat/nodes

2.2.3、 查看所有索引

  1. GET _cat/indices

2.3、常用查询

2.3.1、查询数量

  • track_total_hits=true不然超过1万，数量只给10000
  • customer_remind为索引名称
  • 限制size=0,不反回结果,只返回数量
  • should 相当于mysql中的 or
  • filter 过滤 可以理解成mysql中的 and
  • term 精确匹配 相当于mysql中的 =

  • terms 相当于mysql中的 in

    1. POST customer_remind/_search?track_total_hits=true
    2. {
    3. "query": {
    4.   "bool": {
    5.     "should": [
    6.      {
    7.         "terms": {
    8.           "carIdOwnOrg": [
    9.             "15519724471253495810",
    10.             "15519724471253495811"
    11.           ]
    12.         }
    13.       },
    14.       {
    15.         "terms": {
    16.           "idOwnOrg": [
    17.             "15519724471253495810"
    18.           ]
    19.         }
    20.       }
    21.     ],
    22.     "filter": [
    23.       {
    24.         "terms": {
    25.           "state": [
    26.             "0",
    27.             "2"
    28.           ]
    29.         }
    30.       },
    31.       {
    32.         "term": {
    33.           "groupId": "15519724471253495812"
    34.         }
    35.       }
    36.     ]
    37.   }
    38. },
    39. "size": 0
    40. }

    2.3.2、查询列表

  • customer_remind为索引名称

  • must 必须匹配
  • multi_match 多个字段模糊查询
  • query对应查询的关键词
  • from、size对应分页参数

  • sort 排序参数

    1. POST customer_remind/_search
    2. {
    3. "query": {
    4.   "bool": {
    5.     "must": [
    6.         {
    7.           "multi_match": {
    8.             "query": "16605115059",
    9.             "analyzer": "ik_smart",
    10.             "type": "best_fields",
    11.             "operator": "and",
    12.             "fields": ["customerName","customerCellPhone"]
    13.           }
    14.         }
    15.     ]
    16.   }
    17. },
    18. "from": 0,
    19. "size": 10,
    20. "sort": {
    21.   "creationtime": {
    22.     "order": "desc"
    23.   }
    24. }
    25. }
    1. {
    2. "query": {
    3.   "bool": {
    4.     "must": [
    5.       {
    6.         "match": {
    7.           "customerName": {
    8.             "analyzer": "ik_smart",
    9.             "query": "AAA",
    10.             "operator": "and"
    11.           }
    12.         }
    13.       },
    14.       {
    15.         "match": {
    16.           "customerCellPhone": {
    17.             "analyzer": "ik_smart",
    18.             "query": "A",
    19.             "operator": "and"
    20.           }
    21.         }
    22.       },
    23.       {
    24.         "match": {
    25.           "fullCarNo": {
    26.             "analyzer": "ik_smart",
    27.             "query": "A",
    28.             "operator": "and"
    29.           }
    30.         }
    31.       }
    32.     ]
    33.   }
    34. },
    35. "from": 0,
    36. "size": 10,
    37. "sort": {
    38.   "creationtime": {
    39.     "order": "desc"
    40.   }
    41. }
    42. }

    2.3.3、详情查询

  • _doc/{_id} 根据id查询详情

    1. GET customer_remind/_doc/15748138447761588306

    2.3.4、filter与must，term与match的区别

    2.3.4.1、根据字段类型不同

  • 对于 keyword类型的字段而言， 用 term 和 match 都是可以查询的；

  • 但对于 text 类型的分词字段而言，只能用match才能够查询到结果；

    2.3.4.2、根据嵌套类型查询（filter 与 must 是属于同一个级别的查询方式，都可以作为 query->bool 的属性）

  • filter： 不计算评分，查询效率高、有缓存。（推荐）

    1.      term： 精确匹配<br />           match： 模糊匹配、倒排索引

  • must： 要计算评分，查询效率低、无缓存

    term： 精确匹配、 要评分
    match：模糊匹配、 要评分

    2.4、删除

    2.4.1、删除索引下所有的数据

    1. POST /customer_remind/_delete_by_query
    2. {
    3. "query": {
    4.   "match_all": {}
    5. }
    6. }

    2.4.2、根据id删除单条数据

    1. DELETE /customer_remind/_doc/15748138447761588306

    2.5、更新

    2.5.1、局部更新

    1. POST /customer_remind/_doc/15748138447761588306/_update
    2. {
    3. "doc": {
    4.   "customerName": "名"
    5. }
    6. }

    2.5.2、全量更新

    1. POST /customer_remind/_doc/15748138447761588306
    2. {
    3. "customerName": "名ss"
    4. }

    3、备注

    3.1、浏览器插件

    Elasticvue
    ElasticSearch Head

    3.2、配置

    image.png