ElasticSearch是一個基於Lucene的搜索服務器，它提供了一個分佈式多用戶能力的全文搜索引擎，基於RESTful web接口。Elasticsearch是用Java語言開發的，並作爲Apache許可條款下的開放源碼發佈，是一種流行的企業級搜索引擎。ElasticSearch用於雲計算中，能夠達到實時搜索，穩定，可靠，快速，安裝使用方便。

1.Elasticsearch中的文檔表現

ElasticSearch是面向文檔(document oriented)的，這意味着它可以存儲整個對象或文檔(document)。然而它不僅僅是存儲，還會索引(index)每個文檔的內容使之可以被快速搜索。在ElasticSearch中，你可以對文檔（而非成行成列的數據）進行索引、搜索、排序、過濾，集合及數據分析。

ElasticSearch使用 JSON作爲文檔序列化格式。JSON現在已經被大多語言所支持，而且已經成爲NoSQL數據領域的標準格式。

ElasticSearch的一個文檔不僅包含文檔信息，還包含元數據--有關文檔的信息。元數據的三大元素分別是：

_index：索引庫，類似於關係型數據庫裏的“數據庫”，它是我們存儲和索引關聯數據的地方。

_type：類型，類似於關係型數據庫中的表。可以是大寫或小寫，不能包含下劃線或逗號。

_id：與_index和_type組合時，就可以在ELasticsearch中唯一標識（類似於主鍵）一個文檔。當創建一個文檔，你可以自定義_id，也可以讓Elasticsearch自動生成。

另外，元數據還包括以下信息：

_uid：文檔唯一標識(_type#_id)

_source：文檔原始數據

_all：所有字段的連接字符串

2.Elasticsearch中的服務URL

ElasticSearch中常用的的各種服務的URL地址，如下表所示：

功能	URL	請求方式	說明
集羣相關	/_cat/health?v	GET	查看集羣健康狀態
	/_cat/nodes?v	GET	查看節點健康狀態
	/_cat/indices?v	GET	查看集羣所有索引
	/_cluster/nodes	GET	獲得集羣中所有節點和信息
	/_cluster/health	GET	查看集羣健康狀態
	/_cluster/state	GET	獲得集羣裏的所有信息(集羣信息、節點信息、mapping信息等）
節點相關	/_nodes/process	GET	查看file descriptor的相關信息
	/_nodes/process/stats	GET	統計節點的資源信息（內存、CPU等）
	/_nodes/jvm	GET	獲得各節點的虛擬機統計和配置信息
	/_nodes/jvm/stats	GET	更加詳細的虛擬機信息
	/_nodes/http	GET	獲得各個節點的http信息（如ip地址）
	/_nodes/http/stats	GET	獲得各個節點處理http請求的統計情況
	/_nodes/thread_pool	GET	獲得各種類型的線程池
	/_nodes/thread_pool/stats	GET	獲得各種類型的線程池的統計信息
索引相關	/index/_search	GET,POST	索引查詢
	/index	PUT,DELETE	創建或操作索引
	/_aliases	GET,POST	獲取或操作索引的別名
	/index/_settings	PUT	創建或操作設置(其中number_of_shards不可更改)
	/index/_mapping	PUT	創建或操作mapping
	/index/_open	POST	打開被關閉的索引
	/index/_close	POST	關閉索引
	/index/_refresh	POST	刷新索引（使新加內容對搜索可見）
	/index/_flush	POST	刷新索引，將變動提交到lucene索引文件中並清空elasticsearch的transaction log
	/index/_optimize	POST	優化segement，主要是對索引的segement進行合併
	/index/_status	GET	獲得索引的狀態信息
	/index/_segments	GET	獲得索引的segments的狀態信息
	/index/type/id	PUT,POST,DELETE	操作指定文檔(增刪改查)
	/index/type/id/_create	PUT	創建一個文檔，如果該文件已經存在，則返回失敗
	/index/type/id/_update	POST	更新一個文件，如果改文件不存在，則返回失敗
	/index/type/_bulk	PUT	批量提交數據更新
	/index/type/_mget	GTE	批量獲取指定_id的文檔信息
	/index/_explain	GET	不執行實際搜索，而返回解釋信息
	/index/_analyze	GET	不執行實際搜索，根據輸入的參數進行文本分析

3.ElasticSearch的URL操作

3.1 查看集羣信息

3.1.1 查看集羣健康狀態

GET _cat/health?v

Response:

epoch      timestamp cluster       status node.total node.data shards pri relo init unassign pending_tasks max_task_wait_time active_shards_percent
1565253576 08:39:36  my-es.cluster green           1         1      2   2    0    0        0             0                  -                100.0%

3.1.2 查看節點健康狀態

GET _cat/nodes?v

Response:

ip            heap.percent ram.percent cpu load_1m load_5m load_15m node.role master name
192.168.1.199           36          63   1    0.00    0.14     0.12 mdi       *      node-1

3.1.3 查看集羣所有索引

GET _cat/indices?v

Response:

health status index                uuid                   pri rep docs.count docs.deleted store.size pri.store.size
green  open   .kibana_task_manager aP_xUt7lQD2RdQDuT5ynbw   1   0          2            0     12.5kb         12.5kb
green  open   .kibana_1            -axbsiTwRPmlIVniX-0hOA   1   0          4            1     19.8kb         19.8kb

3.1.4 查看集羣健康狀態

GET _cluster/health

Response:

{
  "cluster_name" : "my-es.cluster",
  "status" : "green",
  "timed_out" : false,
  "number_of_nodes" : 1,
  "number_of_data_nodes" : 1,
  "active_primary_shards" : 2,
  "active_shards" : 2,
  "relocating_shards" : 0,
  "initializing_shards" : 0,
  "unassigned_shards" : 0,
  "delayed_unassigned_shards" : 0,
  "number_of_pending_tasks" : 0,
  "number_of_in_flight_fetch" : 0,
  "task_max_waiting_in_queue_millis" : 0,
  "active_shards_percent_as_number" : 100.0
}

3.2 查看節點信息

3.2.1 查看file descriptor的相關信息

GET _nodes/process

Response:

{
  "_nodes" : {
    "total" : 1,
    "successful" : 1,
    "failed" : 0
  },
  "cluster_name" : "my-es.cluster",
  "nodes" : {
    "SQYgJvIZR7yqA3TzkURejA" : {
      "name" : "node-1",
      "transport_address" : "192.168.1.199:9300",
      "host" : "192.168.1.199",
      "ip" : "192.168.1.199",
      "version" : "6.8.2",
      "build_flavor" : "default",
      "build_type" : "tar",
      "build_hash" : "b506955",
      "roles" : [
        "master",
        "data",
        "ingest"
      ],
      "attributes" : {
        "ml.machine_memory" : "3954188288",
        "xpack.installed" : "true",
        "ml.max_open_jobs" : "20",
        "ml.enabled" : "true"
      },
      "process" : {
        "refresh_interval_in_millis" : 1000,
        "id" : 9496,
        "mlockall" : false
      }
    }
  }
}

3.2.2 獲得各個節點的http信息

GET _nodes/http

Response:

{
  "_nodes" : {
    "total" : 1,
    "successful" : 1,
    "failed" : 0
  },
  "cluster_name" : "my-es.cluster",
  "nodes" : {
    "SQYgJvIZR7yqA3TzkURejA" : {
      "name" : "node-1",
      "transport_address" : "192.168.1.199:9300",
      "host" : "192.168.1.199",
      "ip" : "192.168.1.199",
      "version" : "6.8.2",
      "build_flavor" : "default",
      "build_type" : "tar",
      "build_hash" : "b506955",
      "roles" : [
        "master",
        "data",
        "ingest"
      ],
      "attributes" : {
        "ml.machine_memory" : "3954188288",
        "xpack.installed" : "true",
        "ml.max_open_jobs" : "20",
        "ml.enabled" : "true"
      },
      "http" : {
        "bound_address" : [
          "192.168.1.199:9200"
        ],
        "publish_address" : "192.168.1.199:9200",
        "max_content_length_in_bytes" : 104857600
      }
    }
  }
}

3.3 索引的相關操作

3.3.1創建一個索引，並設置shards和replicas的個數

PUT user_index
{
  "settings": {
    "number_of_replicas": 1,
    "number_of_shards": 1
  }
}

Response:

{
  "acknowledged" : true,
  "shards_acknowledged" : true,
  "index" : "user_index"
}

3.3.2 修改索引的replicas數，shards是不能修改

PUT user_index/_settings
{
  "settings": {
    "number_of_replicas": 2
  }
}

Response:

{
  "acknowledged" : true
}

3.3.3 刪除索引

DELETE user_index

Response:

{
  "acknowledged" : true
}

3.3.4 添加索引關聯別名

POST _aliases
{
  "actions":[{
      "add":{"index":"user_index","alias":"user_alias"}
  }]
}

也可以這樣寫：

PUT user_index/_aliases
{
  "actions":[{
      "add":{"alias":"user_alias"}
  }]
}

3.3.5 刪除索引關聯別名

POST _aliases
{
  "actions":[{
      "remove":{"index":"user_index","alias":"user_alias"}
  }]
}

也可以這樣寫：

PUT user_index/_aliases
{
  "actions":[{
      "remove":{"alias":"user_alias"}
  }]
}

3.3.6查看索引別名信息

GET _aliases

Response:

{
  ".kibana_1" : {
    "aliases" : {
      ".kibana" : { }
    }
  },
  ".kibana_task_manager" : {
    "aliases" : { }
  },
  "user_index" : {
    "aliases" : {
      "user_alias" : { }
    }
  }
}

3.3.7 創建索引mapping

PUT user_index/_mapping/user_type
{
  "dynamic":false,
  "properties": {
    "name":{
      "type": "text",
      "analyzer": "standard"
    },
    "age": {
      "type": "integer"
    },
    "join_date":{
      "type": "date"
    },
    "phone":{
      "type": "keyword"
    },
    "country":{
      "type": "keyword"
    },
    "province":{
      "type": "keyword"
    },
    "city":{
      "type": "keyword"
    },
    "remark":{
      "type": "text",
      "analyzer": "whitespace"
    }
  }
}

3.3.8 添加一個doc文檔，指定doc的_id。

如果沒有指定_id則Elasticsearch會自動創建一個_id的值

PUT user_index/user_type/1
{
  "name":"chen zhuangyuan",
  "age":27,
  "join_date":"2018-01-01",
  "phone":"18823450001",
  "country":"CN",
  "province":"guangdong",
  "city":"guangzhou",
  "remark":"I'm zhuangyuan,I like elasticsearch"
}

Response:

{
  "_index" : "user_index",
  "_type" : "user_type",
  "_id" : "2",
  "_version" : 1,
  "result" : "created",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 20,
  "_primary_term" : 3
}

3.3.9 更新一個doc文檔的值，完全替換更新。

這個和新增一個doc一樣，如果doc存在則完全更新，doc不存在則創建。

PUT user_index/user_type/1
{
  "name":"chen zhuangyuan",
  "age":28
}

更新後_id=1的這個doc的信息如下，其他字段的值已經被清空了。

GET user_index/user_type/1

Response:

{
  "_index" : "user_index",
  "_type" : "user_type",
  "_id" : "1",
  "_version" : 8,
  "_seq_no" : 23,
  "_primary_term" : 3,
  "found" : true,
  "_source" : {
    "name" : "chen zhuangyuan",
    "age" : 28
  }
}

3.3.10 創建一個doc文檔，當且僅當文檔不存在時創建，存在是返回錯誤。

PUT user_index/user_type/3/_create
{
  "name":"zhang fulai",
  "age":28,
  "join_date":"2018-03-01",
  "phone":"18823450003",
  "country":"CN",
  "province":"guangdong",
  "city":"shenzhen",
  "remark":"I'm liaiguo,I like hadoop"
}

Response:

{
  "_index" : "user_index",
  "_type" : "user_type",
  "_id" : "3",
  "_version" : 1,
  "result" : "created",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 25,
  "_primary_term" : 3
}

再次執行，則返回錯誤，創建失敗。

{
  "error": {
    "root_cause": [
      {
        "type": "version_conflict_engine_exception",
        "reason": "[user_type][3]: version conflict, document already exists (current version [1])",
        "index_uuid": "FT3HUBPESD6Yih2o_EddLw",
        "shard": "2",
        "index": "user_index"
      }
    ],
    "type": "version_conflict_engine_exception",
    "reason": "[user_type][3]: version conflict, document already exists (current version [1])",
    "index_uuid": "FT3HUBPESD6Yih2o_EddLw",
    "shard": "2",
    "index": "user_index"
  },
  "status": 409
}

3.3.11 更新一個doc文檔的指定字段的值。

如將_id=3的這個用戶age修改爲29。

POST user_index/user_type/3/_update
{
  "doc": {
     "age":29
  }
}

更新後_id=3的這個doc的信息如下：

GET user_index/user_type/3

Response:

{
  "_index" : "user_index",
  "_type" : "user_type",
  "_id" : "3",
  "_version" : 2,
  "_seq_no" : 26,
  "_primary_term" : 3,
  "found" : true,
  "_source" : {
    "name" : "zhang fulai",
    "age" : 29,
    "join_date" : "2018-03-01",
    "phone" : "18823450003",
    "country" : "CN",
    "province" : "guangdong",
    "city" : "shenzhen",
    "remark" : "I'm liaiguo,I like hadoop"
  }
}

3.3.12 批量提交_bulk。

一次提交增、刪、改的文檔信息，這種操作的效率減少了請求服務器的網絡次數，提高了執行的效率。

PUT user_index/user_type/_bulk
{"index":{"_id":"4"}}
{"name":"guo daming","age":26,"phone":"18823450004","country":"CN","province":"beijing","city":"beijingshi","remark":"I.m from beijing,I like java"}
{"index":{"_id":"5"}}
{"name":"zhao mingming","age":26,"phone":"18823450005","country":"CN","province":"shanghai","city":"shanghaishi","remark":"I.m from shanghai,I like spark"}
{"delete":{"_id":"1"}}
{"update":{"_id":"2"}}
{"doc":{"age":"25"}}

Response:

{
  "took" : 19,
  "errors" : false,
  "items" : [
    {
      "index" : {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "4",
        "_version" : 7,
        "result" : "updated",
        "_shards" : {
          "total" : 2,
          "successful" : 1,
          "failed" : 0
        },
        "_seq_no" : 33,
        "_primary_term" : 3,
        "status" : 200
      }
    },
    {
      "index" : {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "5",
        "_version" : 1,
        "result" : "created",
        "_shards" : {
          "total" : 2,
          "successful" : 1,
          "failed" : 0
        },
        "_seq_no" : 34,
        "_primary_term" : 3,
        "status" : 201
      }
    },
    {
      "delete" : {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "1",
        "_version" : 10,
        "result" : "deleted",
        "_shards" : {
          "total" : 2,
          "successful" : 1,
          "failed" : 0
        },
        "_seq_no" : 27,
        "_primary_term" : 3,
        "status" : 200
      }
    },
    {
      "update" : {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "2",
        "_version" : 8,
        "result" : "updated",
        "_shards" : {
          "total" : 2,
          "successful" : 1,
          "failed" : 0
        },
        "_seq_no" : 35,
        "_primary_term" : 3,
        "status" : 200
      }
    }
  ]
}

另外，如果一次提交的_bulk的參數不在同一個index下，在每一個參數體裏面指定index和type就可以。

PUT _bulk
{"create":{"_index":"user_index","_type":"user_type","_id":"4"}}
{"name":"guo daming","age":26,"phone":"18823450004","country":"CN","province":"beijing","city":"beijingshi","remark":"I.m from beijing,I like java"}
{"create":{"_index":"user_index","_type":"user_type","_id":"5"}}
{"name":"zhao mingming","age":26,"phone":"18823450005","country":"CN","province":"shanghai","city":"shanghaishi","remark":"I.m from shanghai,I like spark"}
{"delete":{"_index":"user_index","_type":"user_type","_id":"1"}}
{"update":{"_index":"user_index","_type":"user_type","_id":"2"}}
{"doc":{"age":"25"}}

3.3.13 Elasticsearch的文檔查詢

3.3.13.1 根據文檔_id獲取。

URL地址格式：index/type/_id

GET user_index/user_type/1

3.3.13.2 批量查詢_mget。

URL地址格式：index/type/_mget。API參數是一個docs數組，數組的每個節點定義一個文檔的_index、_type、_id元數據。如果你只想檢索一個或幾個確定的字段，也可以定義一個_source。

GET _mget
{
  "docs":[{
   "_index":"user_index",
   "_type":"user_type",
   "_id":"1",
   "_source":["name","phone"]
  },
  {
  "_index":"user_index",
  "_type":"user_type",
  "_id":"1",
  "_source":["name","phone"]
  }]
}

Response:

{
  "docs" : [
    {
      "_index" : "user_index",
      "_type" : "user_type",
      "_id" : "1",
      "_version" : 1,
      "_seq_no" : 29,
      "_primary_term" : 3,
      "found" : true,
      "_source" : {
        "phone" : "18823450001",
        "name" : "chen zhuangyuan"
      }
    },
    {
      "_index" : "user_index",
      "_type" : "user_type",
      "_id" : "1",
      "_version" : 1,
      "_seq_no" : 29,
      "_primary_term" : 3,
      "found" : true,
      "_source" : {
        "phone" : "18823450001",
        "name" : "chen zhuangyuan"
      }
    }
  ]
}

另外，也可以使用簡單的參數查詢，通過數組指定文檔的_id。

GET user_index/user_type/_mget
{
  "ids":["1","2","3","4"]
}

3.3.13.3 空查詢，即查詢所有。

如果沒有指定查詢參數，則查詢索引下的所有文檔信息。

GET user_index/user_type/_search
GET user_index/_search
GET _search
GET user_index/user_type/_search
{
  "query": {
    "match_all": {}
  }
}

3.3.13.4 查詢字符串搜索。

如搜索索引中包含elasticsearch的所有文檔信息。

GET user_index/user_type/_search?q=elasticsearch

因爲用戶信息中只有remark字段包含了elasticsearch，因此這個查詢等價於：

GET user_index/user_type/_search?q=remark:elasticsearch

Response:

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 0.6931472,
    "hits" : [
      {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "1",
        "_score" : 0.6931472,
        "_source" : {
          "name" : "chen zhuangyuan",
          "age" : 27,
          "join_date" : "2018-01-01",
          "phone" : "18823450001",
          "country" : "CN",
          "province" : "guangdong",
          "city" : "guangzhou",
          "remark" : "I'm zhuangyuan,I like elasticsearch"
        }
      }
    ]
  }
}

3.3.13.5 請求參數體搜索。

如搜索索引中包含elasticsearch的所有文檔信息。

GET user_index/user_type/_search
{
  "query": {
    "term": {
      "remark": "elasticsearch"
    }
  }
}

GET user_index/user_type/_search
{
 "query": {
   "terms": {
     "remark": [
       "hadoop",
       "spark"
     ]
   }
 }
}

3.3.13.6 分頁查詢From/Size。

通過from和size參數，可以實現分頁查詢。from表示從第幾條開始取，size 表示最多取多少條。from默認值是0，size默認值是10。

GET user_index/user_type/_search
{
 "query": {
   "match": {
     "remark":"spark"
   }
 },
 "from": 0,
 "size": 1
}

Response:

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 0.49917623,
    "hits" : [
      {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "2",
        "_score" : 0.49917623,
        "_source" : {
          "name" : "li aiguo",
          "age" : "25",
          "join_date" : "2018-02-01",
          "phone" : "18823450002",
          "country" : "CN",
          "province" : "guangdong",
          "city" : "shenzhen",
          "remark" : "I'm liaiguo,I like spark"
        }
      }
    ]
  }
}

3.3.13.7 Sort排序。

實現按照指定一個或多個字段進行排序。默認請求下，搜索結果會按照_score的得分進行排序。

GET user_index/user_type/_search
{
 "query": {
   "match": {
     "remark":"spark"
   }
 },
 "sort": [
   {
     "age": {
       "order": "asc"
     },
     "province": {
       "order": "asc"
     }
   }
 ]
}

Response:

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : null,
    "hits" : [
      {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "2",
        "_score" : null,
        "_source" : {
          "name" : "li aiguo",
          "age" : "25",
          "join_date" : "2018-02-01",
          "phone" : "18823450002",
          "country" : "CN",
          "province" : "guangdong",
          "city" : "shenzhen",
          "remark" : "I'm liaiguo,I like spark"
        },
        "sort" : [
          25,
          "guangdong"
        ]
      },
      {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "5",
        "_score" : null,
        "_source" : {
          "name" : "zhao mingming",
          "age" : 26,
          "phone" : "18823450005",
          "country" : "CN",
          "province" : "shanghai",
          "city" : "shanghaishi",
          "remark" : "I.m from shanghai,I like spark"
        },
        "sort" : [
          26,
          "shanghai"
        ]
      }
    ]
  }
}

3.3.13.8 範圍查詢。

如搜索用戶索引中age大於等於27且小於等於30的所有用戶信息，並且結果按照年齡升序排序。

GET user_index/user_type/_search
{
  "query": {
    "range": {
      "age": {
        "gte": 27,
        "lte": 30
      }
    }
  }
  , "sort": [
    {
      "age": {
        "order": "asc"
      }
    }
  ]
}

Response:

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : null,
    "hits" : [
      {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "1",
        "_score" : null,
        "_source" : {
          "name" : "chen zhuangyuan",
          "age" : 27,
          "join_date" : "2018-01-01",
          "phone" : "18823450001",
          "country" : "CN",
          "province" : "guangdong",
          "city" : "guangzhou",
          "remark" : "I'm zhuangyuan,I like elasticsearch"
        },
        "sort" : [
          27
        ]
      },
      {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "3",
        "_score" : null,
        "_source" : {
          "name" : "zhang fulai",
          "age" : 29,
          "join_date" : "2018-03-01",
          "phone" : "18823450003",
          "country" : "CN",
          "province" : "guangdong",
          "city" : "shenzhen",
          "remark" : "I'm liaiguo,I like hadoop"
        },

        "sort" : [
          29
        ]
      }
    ]
  }
}

3.3.13.9 查看索引中的所有文檔總數。

GET user_index/user_type/_count

Response:

{
  "count" : 5,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  }
}

3.13.19 組合多條件查詢

在項目的實際開發中，基本都是組合多條件查詢來滿足實際的需求。elasticsearch提供bool來實現這種需求。主要參數：

must：文檔必須匹配這些條件才能被包含進來。

must_not：文檔必須不匹配這些條件才能被包含進來。

should：如果滿足這些語句中的任意語句將增加_score得分，否則無任何影響。它們主要用於修正每個文檔的相關性得分。

filter：必須匹配，但它以不評分、過濾模式來進行。這些語句對評分沒有貢獻，只是根據過濾標準來排除或包含文檔。

例如：查詢用戶信息中，remark必須包含elasticsearch，並且不包含spark的用戶信息。

GET user_index/user_type/_search
{
  "query": {
    "bool": {
      "must":  {
        "match": {
          "remark": "elasticsearch"
        }
      },
      "must_not": {
         "match":{
           "remark":"spark"
         }
      },
      "should": {
        "match":{
          "age":27
        }
      }
    }
  }
}

Response:

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 1.6931472,
    "hits" : [
      {
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "1",
        "_score" : 1.6931472,
        "_source" : {
          "name" : "chen zhuangyuan",
          "age" : 27,
          "join_date" : "2018-01-01",
          "phone" : "18823450001",
          "country" : "CN",
          "province" : "guangdong",
          "city" : "guangzhou",
          "remark" : "I'm zhuangyuan,I like elasticsearch"
        }
      }
    ]
  }
}

3.13.20 explian評分分析

從elasticsearch的搜索結果顯示來看，展現給我們的是一個按score得分從高到底排好序的結果集。_explain用來幫助分析文檔的score是如何計算出來的。

GET user_index/user_type/_search
{
  "query": {
    "match": {
      "remark": "elasticsearch"
    }
  },
  "explain": true
}

Response:

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 1.0594962,
    "hits" : [
      {
        "_shard" : "[user_index][0]",
        "_node" : "SQYgJvIZR7yqA3TzkURejA",
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "6",
        "_score" : 1.0594962,
        "_source" : {
          "name" : "liu haoqiang",
          "age" : 27,
          "join_date" : "2018-06-01",
          "phone" : "18823450006",
          "country" : "CN",
          "province" : "guangdong",
          "city" : "guangzhou",
          "remark" : "I'm from guangzhou,I like spark and elasticsearch"
        },
        "_explanation" : {
          "value" : 1.059496,
          "description" : "weight(remark:elasticsearch in 0) [PerFieldSimilarity], result of:",
          "details" : [
            {
              "value" : 1.059496,
              "description" : "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
              "details" : [
                {
                  "value" : 1.2039728,
                  "description" : "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
                  "details" : [
                    {
                      "value" : 1.0,
                      "description" : "docFreq",
                      "details" : [ ]
                    },
                    {
                      "value" : 4.0,
                      "description" : "docCount",
                      "details" : [ ]
                    }
                  ]
                },
                {
                  "value" : 0.88,
                  "description" : "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
                  "details" : [
                    {
                      "value" : 1.0,
                      "description" : "termFreq=1.0",
                      "details" : [ ]
                    },
                    {
                      "value" : 1.2,
                      "description" : "parameter k1",
                      "details" : [ ]
                    },
                    {
                      "value" : 0.75,
                      "description" : "parameter b",
                      "details" : [ ]
                    },
                    {
                      "value" : 5.25,
                      "description" : "avgFieldLength",
                      "details" : [ ]
                    },
                    {
                      "value" : 7.0,
                      "description" : "fieldLength",
                      "details" : [ ]
                    }
                  ]
                }
              ]
            }
          ]
        }
      },
      {
        "_shard" : "[user_index][2]",
        "_node" : "SQYgJvIZR7yqA3TzkURejA",
        "_index" : "user_index",
        "_type" : "user_type",
        "_id" : "1",
        "_score" : 0.6931472,
        "_source" : {
          "name" : "chen zhuangyuan",
          "age" : 27,
          "join_date" : "2018-01-01",
          "phone" : "18823450001",
          "country" : "CN",
          "province" : "guangdong",
          "city" : "guangzhou",
          "remark" : "I'm zhuangyuan,I like elasticsearch"
        },
        "_explanation" : {
          "value" : 0.6931472,
          "description" : "weight(remark:elasticsearch in 0) [PerFieldSimilarity], result of:",
          "details" : [
            {
              "value" : 0.6931472,
              "description" : "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
              "details" : [
                {
                  "value" : 0.6931472,
                  "description" : "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
                  "details" : [
                    {
                      "value" : 1.0,
                      "description" : "docFreq",
                      "details" : [ ]
                    },
                    {
                      "value" : 2.0,
                      "description" : "docCount",
                      "details" : [ ]
                    }
                  ]
                },
                {
                  "value" : 1.0,
                  "description" : "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
                  "details" : [
                    {
                      "value" : 1.0,
                      "description" : "termFreq=1.0",
                      "details" : [ ]
                    },
                    {
                      "value" : 1.2,
                      "description" : "parameter k1",
                      "details" : [ ]
                    },
                    {
                      "value" : 0.75,
                      "description" : "parameter b",
                      "details" : [ ]
                    },
                    {
                      "value" : 4.0,
                      "description" : "avgFieldLength",
                      "details" : [ ]
                    },
                    {
                      "value" : 4.0,
                      "description" : "fieldLength",
                      "details" : [ ]
                    }
                  ]
                }
              ]
            }
          ]
        }
      }
    ]
  }
}

3.3.21 _analyze分詞分析

_analyz是Elasticsearch一個非常有用的API，它可以幫助你分析每一個field或者某個analyzer/tokenizer是如何分析和索引一段文字。返回結果字段含義：

token：是一個實際被存儲在索引中的詞

position：指明詞在原文本中是第幾個位置出現的

start_offset，end_offset：表示詞在原文本中佔據的位置。

GET user_index/_analyze
{
  "analyzer": "standard",
  "text": "I'm from shenzhen,I like elasticsearch,spark and hbase"
}

Response:

{
  "tokens" : [
    {
      "token" : "i'm",
      "start_offset" : 0,
      "end_offset" : 3,
      "type" : "<ALPHANUM>",
      "position" : 0
    },
    {
      "token" : "from",
      "start_offset" : 4,
      "end_offset" : 8,
      "type" : "<ALPHANUM>",
      "position" : 1
    },
    {
      "token" : "shenzhen",
      "start_offset" : 9,
      "end_offset" : 17,
      "type" : "<ALPHANUM>",
      "position" : 2
    },
    {
      "token" : "i",
      "start_offset" : 18,
      "end_offset" : 19,
      "type" : "<ALPHANUM>",
      "position" : 3
    },
    {
      "token" : "like",
      "start_offset" : 20,
      "end_offset" : 24,
      "type" : "<ALPHANUM>",
      "position" : 4
    },
    {
      "token" : "elasticsearch",
      "start_offset" : 25,
      "end_offset" : 38,
      "type" : "<ALPHANUM>",
      "position" : 5
    },
    {
      "token" : "spark",
      "start_offset" : 39,
      "end_offset" : 44,
      "type" : "<ALPHANUM>",
      "position" : 6
    },
    {
      "token" : "and",
      "start_offset" : 45,
      "end_offset" : 48,
      "type" : "<ALPHANUM>",
      "position" : 7
    },
    {
      "token" : "hbase",
      "start_offset" : 49,
      "end_offset" : 54,
      "type" : "<ALPHANUM>",
      "position" : 8
    }
  ]
}

Elasticsearch文檔表現及服務API操作

1.Elasticsearch中的文檔表現

2.Elasticsearch中的服務URL

3.ElasticSearch的URL操作

3.1 查看集羣信息

3.1.1 查看集羣健康狀態

3.1.2 查看節點健康狀態

3.1.3 查看集羣所有索引

3.1.4 查看集羣健康狀態

3.2 查看節點信息

3.2.1 查看file descriptor的相關信息

3.2.2 獲得各個節點的http信息

3.3 索引的相關操作

3.3.1創建一個索引，並設置shards和replicas的個數

3.3.2 修改索引的replicas數，shards是不能修改

3.3.3 刪除索引

3.3.4 添加索引關聯別名

3.3.5 刪除索引關聯別名

3.3.6查看索引別名信息

3.3.7 創建索引mapping

3.3.8 添加一個doc文檔，指定doc的_id。

3.3.9 更新一個doc文檔的值，完全替換更新。

3.3.10 創建一個doc文檔，當且僅當文檔不存在時創建，存在是返回錯誤。

3.3.11 更新一個doc文檔的指定字段的值。

3.3.12 批量提交_bulk。

3.3.13 Elasticsearch的文檔查詢

3.3.13.1 根據文檔_id獲取。

3.3.13.2 批量查詢_mget。

3.3.13.3 空查詢，即查詢所有。

3.3.13.4 查詢字符串搜索。

3.3.13.5 請求參數體搜索。

3.3.13.6 分頁查詢From/Size。

3.3.13.7 Sort排序。

3.3.13.8 範圍查詢。

3.3.13.9 查看索引中的所有文檔總數。

3.13.19 組合多條件查詢

3.13.20 explian評分分析

3.3.21 _analyze分詞分析