es与关系数据库的对比，方便理解

es	关系型数据库
index	database
type	table
document	row （行数据）
field	column （列数据）

   传统关系型数据库中，我们是把数据存入一个database里的某个table中，es可以理解为一个文档类型的数据库，每一条数据，就相当于一个文档，所以index用以检索文档，type就相当于table，确定文档位置，就相当于确定这条数据在哪个table中。document就相当于一行数据，field相当于一列数据。

es查询方式

PUT操作

put请求相当于insert与update操作，可以插入或更新数据。
例：

下面展示一些 内联代码片。

PUT /megacorp/employee/1
{
    "first_name" : "John",
    "last_name" :  "Smith",
    "age" :        25,
    "about" :      "I love to go rock climbing",
    "interests": [ "sports", "music" ]
}

此时插入了一条index为megacorp，type为employee，id为1的一条数据。
当这条数据存在时，会更新，相当于update操作。

GET操作

根据id查询

GET /megacorp/employee/1

得到的结果
{
  "_index" :   "megacorp",
  "_type" :    "employee",
  "_id" :      "1",
  "_version" : 1,
  "found" :    true,
  "_source" :  {
      "first_name" :  "John",
      "last_name" :   "Smith",
      "age" :         25,
      "about" :       "I love to go rock climbing",
      "interests":  [ "sports", "music" ]
  }
}

查询全部数据

GET /megacorp/employee/_search

得到的结果
{
   "took":      6,
   "timed_out": false,
   "_shards": { ... },
   "hits": {
      "total":      3,
      "max_score":  1,
      "hits": [
         {
            "_index":         "megacorp",
            "_type":          "employee",
            "_id":            "3",
            "_score":         1,
            "_source": {
               "first_name":  "Douglas",
               "last_name":   "Fir",
               "age":         35,
               "about":       "I like to build cabinets",
               "interests": [ "forestry" ]
            }
         },
         {
            "_index":         "megacorp",
            "_type":          "employee",
            "_id":            "1",
            "_score":         1,
            "_source": {
               "first_name":  "John",
               "last_name":   "Smith",
               "age":         25,
               "about":       "I love to go rock climbing",
               "interests": [ "sports", "music" ]
            }
         },
         {
            "_index":         "megacorp",
            "_type":          "employee",
            "_id":            "2",
            "_score":         1,
            "_source": {
               "first_name":  "Jane",
               "last_name":   "Smith",
               "age":         32,
               "about":       "I like to collect rock albums",
               "interests": [ "music" ]
            }
         }
      ]
   }
}

根据参数过滤

GET /megacorp/employee/_search?q=last_name:Smith

得到的结果
{
   ...
   "hits": {
      "total":      2,
      "max_score":  0.30685282,
      "hits": [
         {
            ...
            "_source": {
               "first_name":  "John",
               "last_name":   "Smith",
               "age":         25,
               "about":       "I love to go rock climbing",
               "interests": [ "sports", "music" ]
            }
         },
         {
            ...
            "_source": {
               "first_name":  "Jane",
               "last_name":   "Smith",
               "age":         32,
               "about":       "I like to collect rock albums",
               "interests": [ "music" ]
            }
         }
      ]
   }
}

使用DSL语句查询（更灵活的查询）

在json结构体中写查询语句query
GET /megacorp/employee/_search
{
    "query" : {
        "match" : {
            "last_name" : "Smith"
        }
    }
}

下篇文章中，重点写写DSL查询语句的使用。