1. Log in to the Data Lake Compute console and select the service region. You need to have the Tencent Cloud admin or financial collaborator permission.
2. Click SuperSQL Engine on the left sidebar to enter the data engine management page.
3. Find the target private engine and click Specconfiguration on the right to enter the configuration modification page, where you can modify the cluster specification and elastic scaling policy.
4. After making changes, click Save to submit the order and make the payment.
Option 2. Data engine details
1. Log in to the Data Lake Compute console and select the service region. You need to have the Tencent Cloud admin or financial collaborator permission.
2. Click SuperSQL Engine on the left sidebar to enter the data engine management page.
3. Locate the private engine that needs to be modified in the SuperSQL Engine, and click the engine name to go to the engine details page. Hover the mouse over the More option in the upper-right corner of the configuration information, and click Scale Configuration Change from the dropdown menu to modify the cluster specifications and scaling policies.
4. Adjust the parameters as needed and click Save.
Modifying the private engine information
1. Log in to the Data Lake Compute console and select the service region. You need to have the Tencent Cloud admin permission.
2. Click SuperSQL Engine on the left sidebar to enter the data engine management page.
3. Locate the private engine that needs to be modified in the data engine, and click the engine name to go to the engine details page. In basic information, the DescriptionInformation is editable. Hover the mouse over the More option in the top-right corner of the configuration information, and click Startup/SuspensionPolicyConfigurations from the dropdown menu to modify the automatic startup and suspension policies.
Note：
Suspension policy: It supports configurations of suspension methods for the pay-as-you-go SuperSQL Engine, including automatic and scheduled suspension policies. No fees will be incurred after suspending a pay-as-you-go engine.
Automatic suspension: The SuperSQL engine will automatically switch to the paused state after 15 minutes of no tasks.
Scheduled policy: You can configure weekly scheduled startup and suspension policies. The system will periodically start and suspend clusters according to the configuration rules.
Suspend after task ends: If the SuperSQL Engine has tasks in progress at the specified time, the system will automatically suspend the engine within 5 minutes after the tasks are completed.
Suspend after automatic pause: If the SuperSQL Engine has tasks in progress at the specified time, the system will pause the tasks and immediately suspend the engine.
4. Adjust the parameters as needed and click Save.
Managing the Startup and Suspension Policies
This feature supports configurations of startup and suspension policies for pay-as-you-go exclusive data engines to facilitate management and cost control.
Note：
Pay-as-you-go data engines will generate fees if not suspended. Suspend unused data engines promptly.
Startup policy: It supports configurations of startup methods for a pay-as-you-go SuperSQL Engine, including automatic startup, manual startup, and scheduled startup.
Automatic startup: After the configuration, if the data engine is in a suspended state, it will automatically start when a task is submitted to it.
Manual startup: After the configuration, if the data engine is in a suspended state, you need to manually start the data engine before processing data tasks.
Scheduled startup: You can configure weekly scheduled startup policies. The system will periodically start clusters according to the configuration rules.
Suspension policy: It supports configurations of suspension methods for pay-as-you-go data engines, including automatic and scheduled suspension policies. No fees will be incurred after suspending a pay-as-you-go SuperSQL engine.
Automatic suspension: After the configuration, the SuperSQL engine defaults to switching to a suspended state 10 minutes after task completion. The trigger time can also be configured.
Periodic policy - You can configure weekly periodic start and suspension policies. The system starts and suspends the cluster periodically based on the configuration rules.
Suspend after Completion: If a task is being executed by the data engine within the specified time, the data engine automatically suspends the task within 5 minutes after the task is completed.
Suspend after Automatic pause: If a task is being executed on the data engine within the specified time, the system suspends the task and immediately suspends the data engine.
Manually suspending/starting a private engine
Note:
Monthly subscribed resources are resident and cannot be suspended.
1. Log in to the Data Lake Compute console and select the service region. You need to have the Tencent Cloud admin permission.
2. Click SuperSQL Engine on the left sidebar to enter the data engine management page.
3. Find the target private engine, click More, and select Start or Suspend in the drop-down list.
Terminating a private engine
You can terminate a data engine that is no longer needed. A monthly subscribed data engine will be returned automatically after termination. For more information, see Refund.
Note:
Note that a pay-as-you-go data engine cannot be recovered once terminated. Proceed with caution.
1. Log in to the Data Lake Compute console and select the service region. You need to have the Tencent Cloud admin permission.
2. Click SuperSQL Engine on the left sidebar to enter the data engine management page.
3. Find the target private engine (only suspended clusters can be terminated), click More, and select Terminate in the drop-down list.
4. Confirm the termination.
Cluster running logs
Data Lake Compute provides running logs within 14 days for private engines to help you stay informed of the start, suspension, and scaling of clusters. Cluster logs mainly include the following content:
Start time: The time when the cluster starts working.
Suspension time: The time when the cluster stops working.
Scale-out record: The time of the cluster scale-out and the number of added clusters.
Scale-in record: The time of the cluster scale-in and the number of removed clusters.
