复合查询使您能够组合现有查询中的数据，然后在显示报告结果之前应用过滤器，聚合等，这些结果显示组合数据集. Composite Query检索现有查询的多个级别的相关信息，并将组合数据显示为单个平展查询结果.
使用Composite Query，您还可以选择 :
选择SQL修剪选项，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子句设置为结果集上的过滤器复合查询.
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，因此组合可以连接或嵌套.
让我们考虑本例中的以下文档.
AndersenFamily 文件如下.
{
"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 文件如下.
{
"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 文件如下.
{
"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
}我们来吧看一下连接查询的例子.
以下是查询将检索第一个孩子 givenName 为Michelle的家庭的ID和位置.
SELECT f.id,f.location FROM Families f WHERE f.children[0].givenName = "Michelle"
执行上述查询时，它会产生以下输出.
[
{
"id": "SmithFamily",
"location": {
"state": "NY",
"county": "Queens",
"city": "Forest Hills"
}
}
]让我们考虑连接查询的另一个例子.
以下是查询y将返回第一个孩子等级大于3的所有文件.
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/"
}
]我们来看看看看嵌套查询的示例.
以下是查询将迭代所有父项，然后返回 familyName 为Smith的文档.
SELECT * FROM p IN Families.parents WHERE p.familyName = "Smith"
当abov执行e查询，它会产生以下输出.
[
{
"familyName": "Smith",
"givenName": "James"
}
]让我们考虑另一个例子嵌套查询.
以下是查询返回所有 familyName .
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" ]
