DocumentDB SQL – 复合 SQL 查询

复合查询使您能够组合来自现有查询的数据，然后在显示报告结果（显示组合数据集）之前应用过滤器、聚合等。复合查询检索关于现有查询的多个级别的相关信息，并将组合数据呈现为单个扁平化查询结果。

使用复合查询，您还可以选择 –

• 选择 SQL 修剪选项以根据用户的属性选择删除不需要的表和字段。

• 设置 ORDER BY 和 GROUP BY 子句。

• 将 WHERE 子句设置为复合查询结果集的过滤器。

可以组合上述运算符以形成更强大的查询。由于 DocumentDB 支持嵌套集合，因此组合可以串联或嵌套。

让我们考虑此示例的以下文档。

AndersenFamily文档如下。

{ 
   "id": "AndersenFamily", 
   "lastName": "Andersen", 
	
   "parents": [ 
      { "firstName": "Thomas", "relationship":  "father" }, 
      { "firstName": "Mary Kay", "relationship":  "mother" } 
   ],
   
   "children": [ 
      { 
         "firstName": "Henriette Thaulow", 
         "gender": "female", 
         "grade": 5, 
         "pets": [ { "givenName": "Fluffy", "type":  "Rabbit" } ] 
      } 
   ],
   
   "location": { "state": "WA", "county": "King", "city": "Seattle" }, 
   "isRegistered": true 
}

SmithFamily文档如下。

{ 
   "id": "SmithFamily", 
	
   "parents": [ 
      { "familyName": "Smith", "givenName": "James" }, 
      { "familyName": "Curtis", "givenName": "Helen" } 
   ],
   
   "children": [ 
      { 
         "givenName": "Michelle", 
         "gender": "female", 
         "grade": 1 
      }, 
		
      { 
         "givenName": "John", 
         "gender": "male", 
         "grade": 7, 
			
         "pets": [ 
            { "givenName": "Tweetie", "type": "Bird" } 
         ] 
      } 
   ],
   
   "location": { 
      "state": "NY", 
      "county": "Queens", 
      "city": "Forest Hills" 
   },
   
   "isRegistered": true 
} 

WakefieldFamily文档如下。

{ 
   "id": "WakefieldFamily", 
	
   "parents": [ 
      { "familyName": "Wakefield", "givenName": "Robin" }, 
      { "familyName": "Miller", "givenName": "Ben" } 
   ],
   
   "children": [ 
      { 
         "familyName": "Merriam", 
         "givenName": "Jesse", 
         "gender": "female", 
         "grade": 6,
			
         "pets": [ 
            { "givenName": "Charlie Brown", "type": "Dog" }, 
            { "givenName": "Tiger", "type": "Cat" }, 
            { "givenName": "Princess", "type": "Cat" } 
         ] 
      },
		
      { 
         "familyName": "Miller", 
         "givenName": "Lisa", 
         "gender": "female", 
         "grade": 3,
			
         "pets": [ 
            { "givenName": "Jake", "type": "Snake" } 
         ] 
      } 
   ],
   
   "location": { "state": "NY", "county": "Manhattan", "city": "NY" }, 
   "isRegistered": false 
} 

我们来看一个串联查询的例子。

以下是将检索第一个孩子givenName是 Michelle的家庭的 id 和位置的查询。

SELECT f.id,f.location 
FROM Families f 
WHERE f.children[0].givenName = "Michelle"

执行上述查询时，会产生以下输出。

[
   { 
      "id": "SmithFamily", 
      "location": { 
         "state": "NY", 
         "county": "Queens", 
         "city": "Forest Hills" 
      }
   }
]

让我们考虑另一个串联查询的例子。

以下是将返回第一个孩子成绩大于 3 的所有文档的查询。

SELECT * 
FROM Families f 
WHERE ({grade: f.children[0].grade}.grade > 3)

执行上述查询时，会产生以下输出。

[ 
   { 
      "id": "WakefieldFamily", 
      "parents": [ 
         { 
            "familyName": "Wakefield", 
            "givenName": "Robin" 
         },
		
         { 
            "familyName": "Miller", 
            "givenName": "Ben"
         } 
      ],
	  
      "children": [ 
         { 
            "familyName": "Merriam", 
            "givenName": "Jesse", 
            "gender": "female", 
            "grade": 6,
				
            "pets": [ 
               { 
                  "givenName": "Charlie Brown", 
                  "type": "Dog" 
               },
				
               { 
                  "givenName": "Tiger", 
                  "type": "Cat" 
               },
				
               { 
                  "givenName": "Princess", 
                  "type": "Cat" 
               } 
            ] 
         }, 
			
         { 
            "familyName": "Miller", 
            "givenName": "Lisa", 
            "gender": "female", 
            "grade": 3,
				
            "pets": [ 
               { 
                  "givenName": "Jake", 
                  "type": "Snake" 
               } 
            ] 
         } 
      ],
	  
      "location": { 
         "state": "NY", 
         "county": "Manhattan",
         "city": "NY" 
      },
	  
      "isRegistered": false, 
      "_rid": "Ic8LAJFujgECAAAAAAAAAA==", 
      "_ts": 1450541623, 
      "_self": "dbs/Ic8LAA==/colls/Ic8LAJFujgE=/docs/Ic8LAJFujgECAAAAAAAAAA==/", 
      "_etag": "\"00000500-0000-0000-0000-567582370000\"", 
      "_attachments": "attachments/" 
   },
	
   { 
      "id": "AndersenFamily", 
      "lastName": "Andersen",
		
      "parents": [ 
         { 
            "firstName": "Thomas", 
            "relationship": "father" 
         },
			
         { 
            "firstName": "Mary Kay", 
            "relationship": "mother" 
         } 
      ],
	  
      "children": [ 
         { 
            "firstName": "Henriette Thaulow", 
            "gender": "female", 
            "grade": 5,
				
            "pets": [ 
               { 
                  "givenName": "Fluffy", 
                  "type": "Rabbit" 
               } 
            ] 
         } 
      ],
	  
      "location": { 
         "state": "WA", 
         "county": "King", 
         "city": "Seattle"
      },
   
      "isRegistered": true, 
      "_rid": "Ic8LAJFujgEEAAAAAAAAAA==", 
      "_ts": 1450541624, 
      "_self": "dbs/Ic8LAA==/colls/Ic8LAJFujgE=/docs/Ic8LAJFujgEEAAAAAAAAAA==/", 
      "_etag": "\"00000700-0000-0000-0000-567582380000\"", 
      "_attachments": "attachments/" 
   } 
]	  

我们来看一个嵌套查询的例子。

以下是将迭代所有父项然后返回familyName为 Smith的文档的查询。

SELECT * 
FROM p IN Families.parents 
WHERE p.familyName = "Smith"

执行上述查询时，会产生以下输出。

[ 
   { 
      "familyName": "Smith", 
      "givenName": "James" 
   } 
]

让我们考虑另一个嵌套查询的例子。

以下是将返回所有familyName的查询。

SELECT VALUE p.familyName
FROM Families f 
JOIN p IN f.parents

执行上述查询时，会产生以下输出。

[ 
   "Wakefield", 
   "Miller", 
   "Smith", 
   "Curtis" 
]