时间戳 SQL 存储变化的数据类型
Time stamped SQL storage of changing data types
我需要在 SQL 数据库中存储各种时间戳数据参数。请参阅下面的典型非标准化数据，其中我显示了五个模拟值（室温、室内湿度、游泳池 pH 值、AHU 供应温度和室内压力）和一个二进制值（光照状态）。
不同的 "customers" 将拥有我在下面用 "address" 字段指出的数据。通常要添加或删除要存储的给定参数。此外，通常会添加一个以前没有存档的新变量（即冷冻水供应温度），并且不可能事先知道将来可能需要存储哪些参数。
一个典型的查询是 return 123 Main Street 102 房间在给定时间跨度内的温度。另一个典型的查询是 return 主街 123 号所有房间的温度、湿度和光照水平。
为每个所需参数向 table 添加列显然没有意义。但我也很难在同一列中存储不同类型的数据。我也很纠结我如何在许多参数中复制房间号并觉得它应该被规范化，但是，其他参数没有关联的房间号，所以我不知道这将如何工作。我还质疑我是否应该创建一个 table 谁的 PK 是建筑物和时间戳的组合，并加入另一个 table 其中包含参数和值（可能还有类型）的列。
应该如何为这些数据建模？
+------------------+-----------------+------------------------+-------+
| Address | Timestamp | Parameter | Value |
+------------------+-----------------+------------------------+-------+
| 123 Main Street | 7/13/2015 16:00 | Room 101 Temperature | 70.99 |
| 123 Main Street | 7/13/2015 16:00 | Room 101 Humidity | 50% |
| 123 Main Street | 7/13/2015 16:00 | Room 101 Light Status | Off |
| 123 Main Street | 7/13/2015 16:00 | Room 102 Temperature | 70.90 |
| 123 Main Street | 7/13/2015 16:00 | Room 102 Humidity | 50% |
| 123 Main Street | 7/13/2015 16:00 | Room 102 Light Status | Off |
| 123 Main Street | 7/13/2015 16:00 | Room 103 Temperature | 69.95 |
| 123 Main Street | 7/13/2015 16:00 | Room 103 Humidity | 49% |
| 123 Main Street | 7/13/2015 16:00 | Room 103 Light Status | Off |
| 123 Main Street | 7/13/2015 16:15 | Room 101 Temperature | 69.65 |
| 123 Main Street | 7/13/2015 16:15 | Room 101 Humidity | 47% |
| 123 Main Street | 7/13/2015 16:15 | Room 101 Light Status | On |
| 123 Main Street | 7/13/2015 16:15 | Room 102 Temperature | 69.18 |
| 123 Main Street | 7/13/2015 16:15 | Room 102 Humidity | 46% |
| 123 Main Street | 7/13/2015 16:15 | Room 102 Light Status | On |
| 123 Main Street | 7/13/2015 16:15 | Room 103 Temperature | 68.49 |
| 123 Main Street | 7/13/2015 16:15 | Room 103 Humidity | 48% |
| 123 Main Street | 7/13/2015 16:15 | Room 103 Light Status | On |
| 123 Main Street | 7/13/2015 16:30 | Room 101 Temperature | 68.93 |
| 123 Main Street | 7/13/2015 16:30 | Room 101 Humidity | 49% |
| 123 Main Street | 7/13/2015 16:30 | Room 101 Light Status | On |
| 123 Main Street | 7/13/2015 16:30 | Room 102 Temperature | 69.44 |
| 123 Main Street | 7/13/2015 16:30 | Room 102 Humidity | 49% |
| 123 Main Street | 7/13/2015 16:30 | Room 102 Light Status | Off |
| 123 Main Street | 7/13/2015 16:30 | Room 103 Temperature | 69.63 |
| 123 Main Street | 7/13/2015 16:30 | Room 103 Humidity | 48% |
| 123 Main Street | 7/13/2015 16:30 | Room 103 Light Status | Off |
| 321 Front Street | 7/14/2015 14:00 | AHU Supply Temperature | 69.96 |
| 321 Front Street | 7/14/2015 14:00 | Swimming Pool PH | 7.19 |
| 321 Front Street | 7/14/2015 14:00 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 14:15 | AHU Supply Temperature | 69.92 |
| 321 Front Street | 7/14/2015 14:15 | Swimming Pool PH | 6.97 |
| 321 Front Street | 7/14/2015 14:15 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 14:30 | AHU Supply Temperature | 70.37 |
| 321 Front Street | 7/14/2015 14:30 | Swimming Pool PH | 6.84 |
| 321 Front Street | 7/14/2015 14:30 | Room 101 Pressure | 0.12 |
| 321 Front Street | 7/14/2015 14:45 | AHU Supply Temperature | 70.80 |
| 321 Front Street | 7/14/2015 14:45 | Swimming Pool PH | 6.70 |
| 321 Front Street | 7/14/2015 14:45 | Room 101 Pressure | 0.12 |
| 321 Front Street | 7/14/2015 15:00 | AHU Supply Temperature | 71.29 |
| 321 Front Street | 7/14/2015 15:00 | Swimming Pool PH | 6.90 |
| 321 Front Street | 7/14/2015 15:00 | Room 101 Pressure | 0.12 |
| 321 Front Street | 7/14/2015 15:15 | AHU Supply Temperature | 72.13 |
| 321 Front Street | 7/14/2015 15:15 | Swimming Pool PH | 7.13 |
| 321 Front Street | 7/14/2015 15:15 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 15:30 | AHU Supply Temperature | 72.84 |
| 321 Front Street | 7/14/2015 15:30 | Swimming Pool PH | 7.01 |
| 321 Front Street | 7/14/2015 15:30 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 15:45 | AHU Supply Temperature | 72.82 |
| 321 Front Street | 7/14/2015 15:45 | Swimming Pool PH | 7.22 |
| 321 Front Street | 7/14/2015 15:45 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 16:00 | AHU Supply Temperature | 72.23 |
| 321 Front Street | 7/14/2015 16:00 | Swimming Pool PH | 7.40 |
| 321 Front Street | 7/14/2015 16:00 | Room 101 Pressure | 0.11 |
+------------------+-----------------+------------------------+-------+
我会选择 3 个表：
Address
-------
address_id
address_name
Location
--------
location_id
location_name
address_id
Measurement
-----------
meauserment_id
location_id
type
timestamp
value
此处所有房间、游泳池和用品都被建模为不同的位置，因此类型将只是 "Temperature"、"Humidity" 等
对于您的查询，您需要在 (location_id, type, timestamp) 上有一个复合二级索引。
如果同一地址可以有很多位置，并且您真的很关心第二类查询的读取性能，那么（假设您可以允许自己忽略同一地址的多个数据点 location_id-type每个时间戳）组织测量的最佳方式是：
Measurement
-----------
address_id
location_id
type
timestamp
value
你的 PK 是 (address_id, location_id, type, timestamp) + 二级索引 (location_id, type, timestamp)。
我需要在 SQL 数据库中存储各种时间戳数据参数。请参阅下面的典型非标准化数据，其中我显示了五个模拟值（室温、室内湿度、游泳池 pH 值、AHU 供应温度和室内压力）和一个二进制值（光照状态）。
不同的 "customers" 将拥有我在下面用 "address" 字段指出的数据。通常要添加或删除要存储的给定参数。此外，通常会添加一个以前没有存档的新变量（即冷冻水供应温度），并且不可能事先知道将来可能需要存储哪些参数。
一个典型的查询是 return 123 Main Street 102 房间在给定时间跨度内的温度。另一个典型的查询是 return 主街 123 号所有房间的温度、湿度和光照水平。
为每个所需参数向 table 添加列显然没有意义。但我也很难在同一列中存储不同类型的数据。我也很纠结我如何在许多参数中复制房间号并觉得它应该被规范化，但是，其他参数没有关联的房间号，所以我不知道这将如何工作。我还质疑我是否应该创建一个 table 谁的 PK 是建筑物和时间戳的组合，并加入另一个 table 其中包含参数和值（可能还有类型）的列。
应该如何为这些数据建模？
+------------------+-----------------+------------------------+-------+
| Address | Timestamp | Parameter | Value |
+------------------+-----------------+------------------------+-------+
| 123 Main Street | 7/13/2015 16:00 | Room 101 Temperature | 70.99 |
| 123 Main Street | 7/13/2015 16:00 | Room 101 Humidity | 50% |
| 123 Main Street | 7/13/2015 16:00 | Room 101 Light Status | Off |
| 123 Main Street | 7/13/2015 16:00 | Room 102 Temperature | 70.90 |
| 123 Main Street | 7/13/2015 16:00 | Room 102 Humidity | 50% |
| 123 Main Street | 7/13/2015 16:00 | Room 102 Light Status | Off |
| 123 Main Street | 7/13/2015 16:00 | Room 103 Temperature | 69.95 |
| 123 Main Street | 7/13/2015 16:00 | Room 103 Humidity | 49% |
| 123 Main Street | 7/13/2015 16:00 | Room 103 Light Status | Off |
| 123 Main Street | 7/13/2015 16:15 | Room 101 Temperature | 69.65 |
| 123 Main Street | 7/13/2015 16:15 | Room 101 Humidity | 47% |
| 123 Main Street | 7/13/2015 16:15 | Room 101 Light Status | On |
| 123 Main Street | 7/13/2015 16:15 | Room 102 Temperature | 69.18 |
| 123 Main Street | 7/13/2015 16:15 | Room 102 Humidity | 46% |
| 123 Main Street | 7/13/2015 16:15 | Room 102 Light Status | On |
| 123 Main Street | 7/13/2015 16:15 | Room 103 Temperature | 68.49 |
| 123 Main Street | 7/13/2015 16:15 | Room 103 Humidity | 48% |
| 123 Main Street | 7/13/2015 16:15 | Room 103 Light Status | On |
| 123 Main Street | 7/13/2015 16:30 | Room 101 Temperature | 68.93 |
| 123 Main Street | 7/13/2015 16:30 | Room 101 Humidity | 49% |
| 123 Main Street | 7/13/2015 16:30 | Room 101 Light Status | On |
| 123 Main Street | 7/13/2015 16:30 | Room 102 Temperature | 69.44 |
| 123 Main Street | 7/13/2015 16:30 | Room 102 Humidity | 49% |
| 123 Main Street | 7/13/2015 16:30 | Room 102 Light Status | Off |
| 123 Main Street | 7/13/2015 16:30 | Room 103 Temperature | 69.63 |
| 123 Main Street | 7/13/2015 16:30 | Room 103 Humidity | 48% |
| 123 Main Street | 7/13/2015 16:30 | Room 103 Light Status | Off |
| 321 Front Street | 7/14/2015 14:00 | AHU Supply Temperature | 69.96 |
| 321 Front Street | 7/14/2015 14:00 | Swimming Pool PH | 7.19 |
| 321 Front Street | 7/14/2015 14:00 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 14:15 | AHU Supply Temperature | 69.92 |
| 321 Front Street | 7/14/2015 14:15 | Swimming Pool PH | 6.97 |
| 321 Front Street | 7/14/2015 14:15 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 14:30 | AHU Supply Temperature | 70.37 |
| 321 Front Street | 7/14/2015 14:30 | Swimming Pool PH | 6.84 |
| 321 Front Street | 7/14/2015 14:30 | Room 101 Pressure | 0.12 |
| 321 Front Street | 7/14/2015 14:45 | AHU Supply Temperature | 70.80 |
| 321 Front Street | 7/14/2015 14:45 | Swimming Pool PH | 6.70 |
| 321 Front Street | 7/14/2015 14:45 | Room 101 Pressure | 0.12 |
| 321 Front Street | 7/14/2015 15:00 | AHU Supply Temperature | 71.29 |
| 321 Front Street | 7/14/2015 15:00 | Swimming Pool PH | 6.90 |
| 321 Front Street | 7/14/2015 15:00 | Room 101 Pressure | 0.12 |
| 321 Front Street | 7/14/2015 15:15 | AHU Supply Temperature | 72.13 |
| 321 Front Street | 7/14/2015 15:15 | Swimming Pool PH | 7.13 |
| 321 Front Street | 7/14/2015 15:15 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 15:30 | AHU Supply Temperature | 72.84 |
| 321 Front Street | 7/14/2015 15:30 | Swimming Pool PH | 7.01 |
| 321 Front Street | 7/14/2015 15:30 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 15:45 | AHU Supply Temperature | 72.82 |
| 321 Front Street | 7/14/2015 15:45 | Swimming Pool PH | 7.22 |
| 321 Front Street | 7/14/2015 15:45 | Room 101 Pressure | 0.11 |
| 321 Front Street | 7/14/2015 16:00 | AHU Supply Temperature | 72.23 |
| 321 Front Street | 7/14/2015 16:00 | Swimming Pool PH | 7.40 |
| 321 Front Street | 7/14/2015 16:00 | Room 101 Pressure | 0.11 |
+------------------+-----------------+------------------------+-------+
我会选择 3 个表：
Address
-------
address_id
address_name
Location
--------
location_id
location_name
address_id
Measurement
-----------
meauserment_id
location_id
type
timestamp
value
此处所有房间、游泳池和用品都被建模为不同的位置，因此类型将只是 "Temperature"、"Humidity" 等
对于您的查询，您需要在 (location_id, type, timestamp) 上有一个复合二级索引。
如果同一地址可以有很多位置，并且您真的很关心第二类查询的读取性能，那么（假设您可以允许自己忽略同一地址的多个数据点 location_id-type每个时间戳）组织测量的最佳方式是：
Measurement
-----------
address_id
location_id
type
timestamp
value
你的 PK 是 (address_id, location_id, type, timestamp) + 二级索引 (location_id, type, timestamp)。