一 前言

如果返回的結(jié)果集中很多符合條件的結(jié)果，那怎么能一眼就能看到我們想要的那個(gè)結(jié)果呢？比如下面網(wǎng)站所示的那樣，我們搜索elasticsearch，在結(jié)果集中，將所有elasticsearch高亮顯示？

如上圖我們搜索百度一樣。我們?cè)撛趺醋瞿兀?/p>

二 準(zhǔn)備數(shù)據(jù)

PUT lqz/doc/4
{
  "name":"石頭",
  "age":29,
  "from":"gu",
  "desc":"粗中有細(xì)，狐假虎威",
  "tags":["粗", "大","猛"]
}

三 默認(rèn)高亮顯示

我們來查詢：

GET lqz/doc/_search
{
  "query": {
    "match": {
      "name": "石頭"
    }
  },
  "highlight": {
    "fields": {
      "name": {}
    }
  }
}

#我們使用highlight屬性來實(shí)現(xiàn)結(jié)果高亮顯示，需要的字段名稱添加到fields內(nèi)即可，elasticsearch會(huì)自動(dòng)幫我們實(shí)現(xiàn)高亮。

結(jié)果如下：

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 1.5098256,
    "hits" : [
      {
        "_index" : "lqz",
        "_type" : "doc",
        "_id" : "4",
        "_score" : 1.5098256,
        "_source" : {
          "name" : "石頭",
          "age" : 29,
          "from" : "gu",
          "desc" : "粗中有細(xì)，狐假虎威",
          "tags" : [
            "粗",
            "大",
            "猛"
          ]
        },
        "highlight" : {
          "name" : [
            "<em>石</em><em>頭</em>"
          ]
        }
      }
    ]
  }
}

上例中，elasticsearch會(huì)自動(dòng)將檢索結(jié)果用標(biāo)簽包裹起來，用于在頁(yè)面中渲染。

四 自定義高亮顯示

GET lqz/chengyuan/_search
{
  "query": {
    "match": {
      "from": "gu"
    }
  },
  "highlight": {
    "pre_tags": "<b class='key' style='color:red'>",
    "post_tags": "</b>",
    "fields": {
      "from": {}
    }
  }
}
上例中，在highlight中，pre_tags用來實(shí)現(xiàn)我們的自定義標(biāo)簽的前半部分，在這里，我們也可以為自定義的標(biāo)簽添加屬性和樣式。post_tags實(shí)現(xiàn)標(biāo)簽的后半部分，組成一個(gè)完整的標(biāo)簽。至于標(biāo)簽中的內(nèi)容，則還是交給fields來完成。

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 0.5753642,
    "hits" : [
      {
        "_index" : "lqz",
        "_type" : "chengyuan",
        "_id" : "1",
        "_score" : 0.5753642,
        "_source" : {
          "name" : "老二",
          "age" : 30,
          "sex" : "male",
          "birth" : "1070-10-11",
          "from" : "gu",
          "desc" : "皮膚黑，武器長(zhǎng)，性格直",
          "tags" : [
            "黑",
            "長(zhǎng)",
            "直"
          ]
        },
        "highlight" : {
          "name" : [
            "<b class='key' style='color:red'>老</b><b class='key' style='color:red'>二</b>"
          ]
        }
      }
    ]
  }
}

需要注意的是：自定義標(biāo)簽中屬性或樣式中的逗號(hào)一律用英文狀態(tài)的單引號(hào)表示，應(yīng)該與外部elasticsearch語(yǔ)法的雙引號(hào)區(qū)分開。

前后端分離，你怎么處理？把<b class='key' style='color:red'>串直接以json格式返回，前端自行渲染

Elasticsearch之聚合查詢

• avg

• max

• min

• sum

avg

# 查詢`from`是`gu`的人的平均年齡。
# select max(age) as my_avg from user；

GET lqz/doc/_search
{
  "query": {
    "match": {
      "from": "gu"
    }
  },
  "aggs": {
    "my_avg": {
      "avg": {
        "field": "age"
      }
    }
  },
  "_source": ["name", "age"]
}

上例中，首先匹配查詢from是gu的數(shù)據(jù)。在此基礎(chǔ)上做查詢平均值的操作，這里就用到了聚合函數(shù)，其語(yǔ)法被封裝在aggs中，而my_avg則是為查詢結(jié)果起個(gè)別名，封裝了計(jì)算出的平均值。那么，要以什么屬性作為條件呢？是age年齡，查年齡的什么呢？是avg，查平均年齡。

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 3,
    "max_score" : 0.6931472,
    "hits" : [
      {
        "_index" : "lqz",
        "_type" : "doc",
        "_id" : "4",
        "_score" : 0.6931472,
        "_source" : {
          "name" : "石頭",
          "age" : 29
        }
      },
      {
        "_index" : "lqz",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.2876821,
        "_source" : {
          "name" : "顧老二",
          "age" : 30
        }
      },
      {
        "_index" : "lqz",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 0.2876821,
        "_source" : {
          "name" : "龍?zhí)灼?quot;,
          "age" : 22
        }
      }
    ]
  },
  "aggregations" : {
    "my_avg" : {
      "value" : 27.0
    }
  }
}

上例中，在查詢結(jié)果的最后是平均值信息，可以看到是27歲。

雖然我們已經(jīng)使用_source對(duì)字段做了過濾，但是還不夠。我不想看都有哪些數(shù)據(jù)，只想看平均值怎么辦？別忘了size!

GET lqz/doc/_search
{
  "query": {
    "match": {
      "from": "gu"
    }
  },
  "aggs": {
    "my_avg": {
      "avg": {
        "field": "age"
      }
    }
  },
  "size": 0, 
  "_source": ["name", "age"]
}

上例中，只需要在原來的查詢基礎(chǔ)上，增加一個(gè)size就可以了，輸出幾條結(jié)果，我們寫上0，就是輸出0條查詢結(jié)果。

{
  "took" : 8,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 3,
    "max_score" : 0.0,
    "hits" : [ ]
  },
  "aggregations" : {
    "my_avg" : {
      "value" : 27.0
    }
  }
}

max

GET lqz/doc/_search
{
  "query": {
    "match": {
      "from": "gu"
    }
  },
  "aggs": {
    "my_max": {
      "max": {
        "field": "age"
      }
    }
  },
  "size": 0
}

上例中，只需要在查詢條件中將avg替換成max即可。

min

GET lqz/doc/_search
{
  "query": {
    "match": {
      "from": "gu"
    }
  },
  "aggs": {
    "my_min": {
      "min": {
        "field": "age"
      }
    }
  },
  "size": 0
}

sum

# 求年齡總和
GET lqz/doc/_search
{
  "query": {
    "match": {
      "from": "gu"
    }
  },
  "aggs": {
    "my_sum": {
      "sum": {
        "field": "age"
      }
    }
  },
  "size": 0
}

分組查詢

現(xiàn)在我想要查詢所有人的年齡段，并且按照15~20，20~25,25~30分組，并且算出每組的平均年齡。

GET lqz/doc/_search
{
  "size": 0, 
  "query": {
    "match_all": {}
  },
  "aggs": {
    "age_group": {
      "range": {
        "field": "age",
        "ranges": [
          {
            "from": 15,
            "to": 20
          },
          {
            "from": 20,
            "to": 25
          },
          {
            "from": 25,
            "to": 30
          }
        ]
      },
      "aggs": {
        "my_avg": {
          "avg": {
            "field": "age"
          }
        }
      }
    }
  }
}

{
 "took" : 1,
 "timed_out" : false,
 "_shards" : {
   "total" : 5,
   "successful" : 5,
   "skipped" : 0,
   "failed" : 0
 },
 "hits" : {
   "total" : 5,
   "max_score" : 0.0,
   "hits" : [ ]
 },
 "aggregations" : {
   "age_group" : {
     "buckets" : [
       {
         "key" : "15.0-20.0",
         "from" : 15.0,
         "to" : 20.0,
         "doc_count" : 1,
         "my_avg" : {
           "value" : 18.0
         }
       },
       {
         "key" : "20.0-25.0",
         "from" : 20.0,
         "to" : 25.0,
         "doc_count" : 1,
         "my_avg" : {
           "value" : 22.0
         }
       },
       {
         "key" : "25.0-30.0",
         "from" : 25.0,
         "to" : 30.0,
         "doc_count" : 2,
         "my_avg" : {
           "value" : 27.0
         }
       }
     ]
   }
 }
}

上例中，在aggs的自定義別名age_group中，使用range來做分組，field是以age為分組，分組使用ranges來做，from和to是范圍，我們根據(jù)需求做出三組。在分組下面，我們使用aggs對(duì)age做平均數(shù)處理，這樣就可以了。返回的結(jié)果中可以看到，已經(jīng)拿到了三個(gè)分組。doc_count為該組內(nèi)有幾條數(shù)據(jù)，此次共分為三組，查詢出4條內(nèi)容。還有一條數(shù)據(jù)的age屬性值是30，不在分組的范圍內(nèi)！