Azure CosmosDB (12) 创建Cosmos DB并执行查询语句,Windows Azure Platform 系列文章目录
《Windows Azure Platform 系列文章目录》
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在本章节，我们将使用Azure Portal，创建1个Azure Cosmos DB。
1.首先，我们登录Azure China Portal: https://portal.azure.cn
2.选择Azure Cosmos DB
3.创建新的资源组，命名为cosmos-rg
创建新的account name：leicosmos
API设置为Core(SQL)
4.CosmosDB暂时不选择虚拟网络，图略。
注意：创建完毕后，cosmos DB并不会开始收费，因为我们没有分配RU
5.创建完毕后，我们选择该资源，点击Data Explorer
点击New Database，我们输入新的database id
如上图所示，RU可以分配在Database级别。这样Database下面的所有Collection都共享这个Database的RU
我们这里暂时不勾选Provision throughput。
注意：创建Database完毕后，cosmos DB并不会开始收费，因为我们没有分配RU
6.在上一步操作完毕后，我们点击Products，点击右键，New Collection
7.在右侧弹出的窗口中，输入下面的信息：
我们定义了Partition Key分区键为/country，
Throughput最小为400
定义了Unique Keys为/productionId
这个操作完毕后，cosmos DB已经开始收费，因为我们已经分配RU
8.创建完毕后，界面展示如下：
Database Level为Products
Collection Level为clothing
9.我们可以在界面上，插入新的Document。如下图：
10.我们插入第一条数据
{ "id": "1", "productId": "33218896", "country":"China", "category": "Women's Clothing", "manufacturer": "Contoso Sport", "description": "Quick dry crew neck t-shirt", "price": "14.99", "shipping": { "weight": 1, "dimensions": { "width": 6, "height": 8, "depth": 1 } } }
点击Save保存。
执行成功后，截图如下：
10.然后我们重复步骤9中的New Document，插入第二条数据
请注意：我们在步骤7中，创建新的Collection的时候，定义了Unique Key为productId
表示在同一个Partition Key中，productId不能重复
观察下面的数据中，"country":"China"，是与步骤9中的数据，保存在同一个Partition Key里
"productId": "33218896"，是与上面步骤9中的数据相同
{ "id": "2", "productId": "33218896", "country":"China", "category": "Women's Outerwear", "manufacturer": "Contoso", "description": "Black wool pea-coat", "price": "49.99", "shipping": { "weight": 2, "dimensions": { "width": 8, "height": 11, "depth": 3 } } }
执行Save操作，会出现约束错误
11.我们在修改productId为33218897。插入下面的值
{ "id": "2", "productId": "33218897", "country":"China", "category": "Women's Outerwear", "manufacturer": "Contoso", "description": "Black wool pea-coat", "price": "49.99", "shipping": { "weight": 2, "dimensions": { "width": 8, "height": 11, "depth": 3 } } }
执行成功
12.我们还可以插入其他值：
{ "id": "3", "productId": "33218898", "country":"US", "category": "Women's Outerwear", "manufacturer": "Contoso", "description": "Black wool pea-coat", "price": "29.99", "shipping": { "weight": 1, "dimensions": { "width": 9, "height": 4, "depth": 9 } } }
这样一共就插入了三个数据
Query
13.我们执行下面的语句：
SELECT * FROM Products c where c.id="1"
查询结果
[ { "id": "1", "productId": "33218896", "country": "China", "category": "Women's Clothing", "manufacturer": "Contoso Sport", "description": "Quick dry crew neck t-shirt", "price": "14.99", "shipping": { "weight": 1, "dimensions": { "width": 6, "height": 8, "depth": 1 } }, "_rid": "BekdAKyBIekBAAAAAAAAAA==", "_self": "dbs/BekdAA==/colls/BekdAKyBIek=/docs/BekdAKyBIekBAAAAAAAAAA==/", "_etag": "\"00001a00-0000-4200-0000-5cb6e4dd0000\"", "_attachments": "attachments/", "_ts": 1555490013 } ]
14.我们执行下面的语句
SELECT p.id, p.manufacturer, p.description FROM Products p WHERE p.id ="1"
执行结果：
[ { "id": "1", "manufacturer": "Contoso Sport", "description": "Quick dry crew neck t-shirt" } ]
FROM
15.我们执行下面的语句：
SELECT * FROM Products.shipping
执行结果：
[ { "weight": 1, "dimensions": { "width": 6, "height": 8, "depth": 1 } }, { "weight": 2, "dimensions": { "width": 8, "height": 11, "depth": 3 } }, { "weight": 1, "dimensions": { "width": 9, "height": 4, "depth": 9 } } ]
16.我们执行下面的语句
SELECT * FROM Products.shipping.weight
执行结果
[ 1, 2, 1 ]
WHERE
17.我们执行下面的语句
SELECT p.description FROM Products p WHERE p.id = "1"
执行结果
[ { "description": "Quick dry crew neck t-shirt" } ]
Order By clause
18.我们执行下面的语句
SELECT p.price, p.description, p.productId
FROM Products p
ORDER BY p.price ASC
执行结果：
[ { "price": "14.99", "description": "Quick dry crew neck t-shirt", "productId": "33218896" }, { "price": "29.99", "description": "Black wool pea-coat", "productId": "33218898" }, { "price": "49.99", "description": "Black wool pea-coat", "productId": "33218897" } ]
JOIN
19.我们执行下面的语句：
SELECT p.productId
FROM Products p
JOIN p.shipping
执行结果：
[ { "productId": "33218896" }, { "productId": "33218897" }, { "productId": "33218898" } ]
