Elasticsearch学习之路(四)_文档的CRUD

文档的CRUD

	Elasticsearch通过REST API进行文档的CRUD

操作	API示例	备注
Index	PUT my_index/_doc/1 {“user”:“mike”,“comment”:“评论”}	Type名，约定都用_doc Index：如果ID不存在，创建新的文档，否则，先删除现有的文档，再创建新的文档，版本会增加
Create	PUT my_index/_create/1 {“user”:“mike”,“comment”:“评论”} PUT my_index/ _doc(不指定ID，自动生成){“user”:“mike”,“comment”:“评论”}	Create 如果ID已经存在，会失败
Read	GET my_indx/_doc/1	获取对应id文档的数据
Update	POST my_index/_update/1 {“user”:“mike”,“comment”:“评论”}	Update:文档必须已经存在，更新只会对相应字段做增量修改
Delete	DELETE my_index/_doc/1	删除对应id文档

测试API

	在kibana的侧边栏有个开发工具，可以方便我们测试Elasticsearch的API
	我们在之前导入过一个电影的索引数据，现在我们以它为例，测试下相关的API

Index 操作

PUT /movies/_doc/1 
{
  "genre" : [
      "Adventure",
      "Animation",
      "Children",
      "Comedy",
      "Fantasy"
    ],
    "year" : 1995,
    "id" : "1",
    "@version" : "1",
    "title" : "Toy Story"
}

响应结果如下：

{
  "_index" : "movies",
  "_type" : "_doc",
  "_id" : "1",
  "_version" : 2,
  "result" : "updated",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 9743,
  "_primary_term" : 1
}

Create操作

PUT /movies/_create/1  #创建文档,如果文档存在会报错
{
  "genre" : [
      "Adventure",
      "Animation",
      "Children",
      "Comedy",
      "Fantasy"
    ],
    "year" : 1995,
    "id" : "1",
    "@version" : "1",
    "title" : "Toy Story"
}

响应结果如下：
{
  "error" : {
    "root_cause" : [
      {
        "type" : "version_conflict_engine_exception",
        "reason" : "[1]: version conflict, document already exists (current version [2])",
        "index_uuid" : "Km35tJDlTPGjIjnmNgPQ4A",
        "shard" : "0",
        "index" : "movies"
      }
    ],
    "type" : "version_conflict_engine_exception",
    "reason" : "[1]: version conflict, document already exists (current version [2])",
    "index_uuid" : "Km35tJDlTPGjIjnmNgPQ4A",
    "shard" : "0",
    "index" : "movies"
  },
  "status" : 409
}

Read操作

 GET movies/_doc/1   # 获取movies索引中id为1的文档数据
 
 响应结果如下：

{
  "_index" : "movies",
  "_type" : "_doc",
  "_id" : "1",
  "_version" : 1,
  "_seq_no" : 128,
  "_primary_term" : 1,
  "found" : true,
  "_source" : {
    "genre" : [
      "Adventure",
      "Animation",
      "Children",
      "Comedy",
      "Fantasy"
    ],
    "year" : 1995,
    "id" : "1",
    "@version" : "1",
    "title" : "Toy Story"
  }
}

Update 操作

# update操作可以修改原来字段的值，也可以新增字段，但整体请求需要包裹在doc下面
POST movies/_update/1
{
  "doc": {
   "genre" : [
        "Adventure1",
        "Animation1",
        "Children1",
        "Comedy1",
        "Fantasy1"
      ],
    "year" : 1995,
    "id" : "1",
    "@version" : "2",
    "title" : "Toy Story"
  }
}

响应结果如下：
{
  "_index" : "movies",
  "_type" : "_doc",
  "_id" : "1",
  "_version" : 3,
  "result" : "updated",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 9744,
  "_primary_term" : 1
}

Delete 操作

DELETE /movies/_doc/1

响应结果如下：
{
  "_index" : "movies",
  "_type" : "_doc",
  "_id" : "1",
  "_version" : 4,
  "result" : "deleted",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 9745,
  "_primary_term" : 1
}

Bulk API

	Rest API在每次发烧请求的时候，需要重新建立连接，是很消耗性能的，能不能在一个请求中，对一个索引进行不同操作，乃至对不同索引进行不同操作，这就是Bulk API
	
	Bulk API支持四种类型操作：
		1. Index
		2. Create
		3. Update
		4. Delete

	特点：
		1. Bulk API可以在URL中知道Index，也可以在请求体中进行指定
		2. 单条操作失败，并不会影响其他操作结果
		3. 返回结果包含了每一条操作执行的结果

示例

POST _bulk
# 创建一个索引名为test，文档id为1，数据为{"field1":"value1"}的索引
{"index":{"_index":"test","_id":"1"}}
{"field1":"value1"} 
# 删除test索引中id为2的文档(此时还不存在，会报错，但不影响别的执行成功)
{"delete":{"_index":"test","_id":2}} 
# 创建一个索引名为test2，文档id为3，数据为{"field1":"value3"}的索引
{"create":{"_index":"test2","_id":"3"}}
{"field1":"value3"} 
# 将索引为test2的id为的文档更新为新数据
{"update":{"_index":"test","_id":"1"}} 
{"doc":{"field1":"value2"}}

响应结果如下：
对于每个操作，都会有一个响应结果
{
  "took" : 522,
  "errors" : false,
  "items" : [
    {
      "index" : {
        "_index" : "test",
        "_type" : "_doc",
        "_id" : "1",
        "_version" : 3,
        "result" : "updated",
        "_shards" : {
          "total" : 2,
          "successful" : 1,
          "failed" : 0
        },
        "_seq_no" : 2,
        "_primary_term" : 1,
        "status" : 200
      }
    },
    {
      "delete" : {
        "_index" : "test",
        "_type" : "_doc",
        "_id" : "2",
        "_version" : 1,
        "result" : "not_found",
        "_shards" : {
          "total" : 2,
          "successful" : 1,
          "failed" : 0
        },
        "_seq_no" : 3,
        "_primary_term" : 1,
        "status" : 404
      }
    },
    {
      "create" : {
        "_index" : "test2",
        "_type" : "_doc",
        "_id" : "3",
        "_version" : 1,
        "result" : "created",
        "_shards" : {
          "total" : 2,
          "successful" : 1,
          "failed" : 0
        },
        "_seq_no" : 0,
        "_primary_term" : 1,
        "status" : 201
      }
    },
    {
      "update" : {
        "_index" : "test",
        "_type" : "_doc",
        "_id" : "1",
        "_version" : 4,
        "result" : "updated",
        "_shards" : {
          "total" : 2,
          "successful" : 1,
          "failed" : 0
        },
        "_seq_no" : 4,
        "_primary_term" : 1,
        "status" : 200
      }
    }
  ]
}

批量读取 mget

# 1. 批量操作，可以减少网络连接所产生的开销，提高性能
# 读取test索引和test2索引，id都为1的文档

GET _mget
{
  "docs":[
    {"_index":"test",
      "_id":"1"
    },
    {
      "_index":"test2",
      "_id":"1"
    }
  ]
}

响应结果如下：
{
  "docs" : [
    {
      "_index" : "test",
      "_type" : "_doc",
      "_id" : "1",
      "_version" : 4,
      "_seq_no" : 4,
      "_primary_term" : 1,
      "found" : true,
      "_source" : {
        "field1" : "value2"
      }
    },
    {
      "_index" : "test2",
      "_type" : "_doc",
      "_id" : "1",
      "found" : false
    }
  ]
}

Search API

1. 查询是一大块内容，碍于篇幅限制，我将在下个章节详细介绍

常见错误返回

问题	原因
无法连接	网络故障或者集群挂了
连接无法关闭	网络故障或者节点出错
429	集群过于繁忙
4xx	请求体格式有错
500	集群内部错误

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