DataService Studio's cold data storage feature allows you to view custom storage tables. This topic outlines the process for creating and managing these tables and their data.
Create custom storage tables
Access the IoT Platform console.
On the Instance Overview page, locate the desired Enterprise Edition instance and click it to open the Instance Details page.
In the left-side navigation pane, choose DataService Studio > Data Storage.
Navigate to the Data Storage page and select the Offline Storage tab.
Navigate to the Cold Data Storage tab and single click Custom Storage Tables.
Under the Custom Storage Tables tab, single click Create Custom Storage Table.
In the Create Custom Storage Table dialog box, fill in the following settings:
Parameter
Example
Required
Description
Table Display Name
Daily Average Temperature Storage Table
Yes
Enter a name for the storage table, which cannot start with a number or underscore (_), and may include Chinese characters, English letters, numbers, and underscores (_), up to 30 characters.
Table Identifier
DailyAverageTemperature
Yes
Specify the identifier for the storage table, which must begin with an English letter and can include English letters, numbers, and underscores (_), up to 30 characters.
Description
Average temperature of the thermometer
No
Provide a brief description of the storage table's purpose.
Data Retention Period
More
No
The retention period of data in the storage table.
Data older than the specified period will be automatically deleted by the system, according to the time field within the table.
Options include One Month, Two Months, Three Months, Half a Year, One Year, Permanent, and More.
Selecting More requires you to specify both Time Unit and Time Value.
Time Unit
Year
No
Choose the time unit for data retention from Year, Month, or Day.
Time Value
10
No
Enter a positive integer for the time value. Maximum limits are 102 for Year, 2142 for Month, and 64260 for Day.
Year: 102.
Month: 2142.
Day: 64260.
To finalize the creation of the custom storage table, single click Confirm.
Once created, the custom storage table is ready to store data from real-time pipelines.
Manage custom storage tables
To manage custom storage tables, go to the Custom Storage Tables tab, locate the desired table in the storage list, and single click the corresponding operation button to execute the desired action.
To View a table:
ImportantCustom storage tables can be applied to various data analysis features. Keep in mind:
Tables without data output can only serve as output objects for data pipelines or SQL analysis tasks.
Tables with existing data can be used as query objects for multiple SQL analysis tasks, and as data sources for data APIs and visualization reports.
If the table is not referenced by a data pipeline or SQL analysis task, you can view only the Table Name and Chinese Name.
If the table is referenced by a data pipeline or SQL analysis task, you can view its Basic Information and Table Structure.
Basic Information
Item
Example
Description
Table Identifier
${system.device_group_relation}
The unique identifier for the storage table.
Table Display Name
Device Group Relationship Table
The display name of the storage table.
Number of Fields
8
The total number of fields in the storage table.
Data Source
System Data Source
The origin of the data, which can be:
System Data Source: Originates from system tables.
Product Property Data Source, Product Event Data Source: Comes from time series or snapshot tables.
Description
This table outlines the relationship between devices and groups.
The purpose and content of the storage table.
Table Structure: Provides details on the storage table's fields, including names and types.
To Edit a table:
ImportantOnce a table is referenced by a data pipeline or SQL analysis task, it cannot be edited.
To Delete a table:
ImportantYou cannot delete a table that is currently in use. First, stop any related data pipelines or SQL analysis tasks.
To access the Data Overview:
After applying the custom storage table to a real-time pipeline or SQL analysis task, you can preview the latest 20 entries.
To perform Static Data Import:
ImportantStatic data can only be imported after the storage table is successfully initialized.
To Export data:
ImportantData can only be exported after the storage table is successfully initialized.
Under the same account, only one export task can be active at a time, with a daily limit of three export tasks, each supporting up to three downloads.
What to do next
After creating a custom storage table, you can populate it with data by using it as an output object for a data pipeline or SQL analysis task.
Once the custom storage table begins outputting data, it can serve as a query object for multiple SQL analysis tasks, as well as a data source for data APIs and visualization reports.