Creating an Elastic Resource Pool and Creating Queues Within It
An elastic resource pool offers compute resources (CPU and memory) required for running DLI jobs, which can adapt to the changing demands of services.
You can create multiple queues within an elastic resource pool. These queues are associated with specific jobs and data processing tasks, and serve as the basic unit for resource allocation and usage within the pool. This means queues are specific compute resources required for executing jobs.
Queues within an elastic resource pool can be shared to execute jobs. This is achieved by correctly setting the queue allocation policy. This enhances queue utilization. This section describes how to create an elastic resource pool and create queues within it.
Notes and Constraints
- The billing mode of an elastic resource pool cannot be changed.
- The region of an elastic resource pool cannot be changed.
- For a pay-per-use resource pool, the dedicated resource mode is selected by default. The resource pool is billed by calendar hour since it is created.
- Jobs of Flink 1.10 or later can run in elastic resource pools.
- The CIDR block of an elastic resource pool cannot be changed once set.
- Associating an elastic resource pool with a queue:
- Only pay-per-use queues (including dedicated queues) can be associated with elastic resource pools.
- No resources are frozen.
- Currently, only yearly/monthly elastic resource pools can be scaled.
- You can only view the scaling history of resource pools in the last 30 days.
- Elastic resource pools cannot access the Internet.
- Changes to elastic resource pool CUs can occur when setting the CU, adding or deleting queues in an elastic resource pool, or modifying the scaling policies of queues in an elastic resource pool, or when the system automatically triggers elastic resource pool scaling. However, in some cases, the system cannot guarantee that the scaling will reach the target CUs as planned.
- If there are not enough physical resources, an elastic resource pool may not be able to scale out to the desired target size.
- The system does not guarantee that an elastic resource pool will be scaled in to the desired target size.
The system checks the resource usage before scaling in the elastic resource pool to determine if there is enough space for scaling in. If the existing resources cannot be scaled in according to the minimum scaling step, the pool may not be scaled in successfully or only partially.
The scaling step may vary depending on the resource specifications, usually 16 CUs, 32 CUs, 48 CUs, 64 CUs, etc.
For example, if the elastic resource pool has a capacity of 192 CUs and the queues in the pool are using 68 CUs due to running jobs, the plan is to scale in to 64 CUs.
When executing a scaling in task, the system determines that there are 124 CUs remaining and scales in by the minimum step of 64 CUs. However, the remaining 60 CUs cannot be scaled in any further. Therefore, after the elastic resource pool executes the scaling in task, its capacity is reduced to 128 CUs.
Creating an Elastic Resource Pool
- In the navigation pane on the left, choose Resources > Resource Pool.
- On the displayed page, click Buy Resource Pool in the upper right corner.
- On the displayed page, set the following parameters:
Table 1 Parameters Parameter
Description
Region
Select a region. Select a region near you to ensure the lowest latency possible.
Project
Each region corresponds to a project.
Name
Name of the elastic resource pool.
- Only numbers, letters, and underscores (_) are allowed. The value cannot contain only numbers or start with an underscore (_) or number.
- The value can contain a maximum of 128 characters.
NOTE:The elastic resource pool name is case-insensitive. Uppercase letters will be automatically converted to lowercase letters.
Type
- Basic: 16 to 64 CUs
- This edition is suitable for testing scenarios with low resource consumption and low requirements for resource reliability and availability.
- High reliability and availability are not supported.
- Queue properties and job priorities cannot be set.
- Notebook instances cannot be interconnected with.
- Standard: 64 CUs or higher
This edition offers powerful computing capabilities, high availability, and flexible resource management. It is suitable for large-scale computing tasks and business scenarios with long-term resource planning needs.
CU Range
The maximum and minimum CUs allowed for the elastic resource pool.
CU settings are used to control the maximum and minimum CU ranges for elastic resource pools to avoid unlimited resource scaling.
- The total minimum CUs of all queues in an elastic resource pool must be no more than the minimum CUs of the pool.
- The maximum CUs of any queue in an elastic resource pool must be no more than the maximum CUs of the pool.
In CU Range, set the minimum CUs on the left and the maximum CUs on the right.
An elastic resource pool should at least ensure that all queues in it can run with the minimum CUs and should try to ensure that all queues in it can run with the maximum CUs.
The specifications of an elastic resource pool are equal to the minimum CUs allocated during creation. This means that when the elastic resource pool is first created, the actual CUs will be equal to the specifications, which is also the minimum CUs.
Description
Description of the elastic resource pool
CIDR Block
CIDR block the elastic resource pool belongs to. If you use an enhanced datasource connection, this CIDR block cannot overlap that of the data source. Once set, this CIDR block cannot be changed.
Recommended CIDR block:
10.0.0.0–10.255.0.0/16–19
172.16.0.0–172.31.0.0/16–19
192.168.0.0–192.168.0.0/16–19
Enterprise Project
If the created elastic resource pool belongs to an enterprise project, select the enterprise project.
Enterprise projects let you manage cloud resources and users by project.
For how to set enterprise projects, see the Enterprise Management User Guide.
NOTE:This parameter is displayed only for users who have enabled the Enterprise Management Service.
Tags
Tags used to identify cloud resources. A tag includes the tag key and tag value. If you want to use the same tag to identify multiple cloud resources, that is, to select the same tag from the drop-down list box for all services, you are advised to create predefined tags on the Tag Management Service (TMS).
If your organization has configured tag policies for DLI, add tags to resources based on the policies. If a tag does not comply with the tag policies, resource creation may fail. Contact your organization administrator to learn more about tag policies.
For details, see Tag Management Service User Guide.
NOTE:- A maximum of 20 tags can be added.
- Only one tag value can be added to a tag key.
- The key name in each resource must be unique.
- Tag key: Enter a tag key name in the text box.
NOTE:
A tag key can contain a maximum of 128 characters. Only letters, numbers, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
- Tag value: Enter a tag value in the text box.
NOTE:
A tag value can contain a maximum of 255 characters. Only letters, numbers, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
- Click Buy and confirm the configurations.
- Click Pay. Wait until the status of the elastic resource pool changes to Available. The elastic resource pool is successfully created.
- Refer to Example Use Case: Creating an Elastic Resource Pool and Running Jobs and Example Use Case: Configuring Scaling Policies for Queues in an Elastic Resource Pool to perform subsequent operations as needed.
Procedure
Create one or more queues within an elastic resource pool to run jobs. This section describes how to create a queue within an elastic resource pool.
Queues added to an elastic resource pool are not billed separately, but billed as billing items of the elastic resource pool.
- In the navigation pane on the left, choose Resources > Resource Pool.
- Locate the target elastic resource pool and click Add Queue in the Operation column.
- On the Add Queue page, configure basic queue information. The following table describes the parameters.
Table 2 Queue information Parameter
Description
Name
Name of the queue to add
Type
- For SQL: The queue is used to run SQL jobs.
- General general purpose: The queue is used to run Spark and Flink jobs.
Engine
If Type is For SQL, the queue engine can be spark or trino.
Enterprise Project
Select the enterprise project the queue belongs to. Queues under different enterprise projects can be added to an elastic resource pool.
Enterprise projects let you manage cloud resources and users by project.
For how to set enterprise projects, see the Enterprise Management User Guide.
NOTE:This parameter is displayed only for users who have enabled the Enterprise Management Service.
Description
Description about the queue.
Tags
Tags used to identify cloud resources. A tag includes the tag key and tag value. If you want to use the same tag to identify multiple cloud resources, that is, to select the same tag from the drop-down list box for all services, you are advised to create predefined tags on the Tag Management Service (TMS).
If your organization has configured tag policies for DLI, add tags to resources based on the policies. If a tag does not comply with the tag policies, resource creation may fail. Contact your organization administrator to learn more about tag policies.
For details, see Tag Management Service User Guide.
NOTE:- A maximum of 20 tags can be added.
- Only one tag value can be added to a tag key.
- The key name in each resource must be unique.
- Tag key: Enter a tag key name in the text box.
NOTE:
A tag key can contain a maximum of 128 characters. Only letters, numbers, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_.
- Tag value: Enter a tag value in the text box.
NOTE:
A tag value can contain a maximum of 255 characters. Only letters, numbers, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.
- Click Next. On the displayed page, configure a scaling policy for the queue in the elastic resource pool.
Figure 1 Configuring a scaling policy when adding a queue
Click Create to add a scaling policy with specified priority, period, Minimum CUs, and Maximum CUs. The parameters of each scaling policy are as follows:
Table 3 Auto scaling policy Parameter
Description
Priority
Priority of the scaling policy in the current elastic resource pool. A larger value indicates a higher priority. You can set a number ranging from 1 to 100.
Period
Time segment when the policy takes effect. It can be set only by hour. The start time is on the left, and the end time is on the right.
- The time range includes the start time but not the end time, that is, [start time, end time).
For example, if the Period to 01 and 17, the scaling policy takes effect at 01:00 a.m. till 05:00 p.m.
- The periods of scaling policies with different priorities cannot overlap.
Min CU
Minimum number of CUs allowed by the scaling policy.
- In any time segment of a day, the total minimum CUs of all queues in an elastic resource pool cannot be more than the minimum CUs of the pool.
- If the minimum CUs of the queue is less than 16 CUs, both Max. Spark Driver Instances and Max. Prestart Spark Driver Instances set in the queue properties do not apply. Refer to Setting Queue Properties.
Max CU
Maximum number of CUs allowed by the scaling policy.
In any time segment of a day, the maximum CUs of any queue in an elastic resource pool cannot be more than the maximum CUs of the pool.
- The first scaling policy is the default policy, and its Period parameter configuration cannot be deleted or modified.
- Flink jobs cannot trigger automatic scaling of queues in an elastic resource pool.
- The time range includes the start time but not the end time, that is, [start time, end time).
- Click OK. View all queues and scaling policies added to the elastic resource pool by referring to Adjusting Scaling Policies for Queues in an Elastic Resource Pool.
Feedback
Was this page helpful?
Provide feedbackThank you very much for your feedback. We will continue working to improve the documentation.See the reply and handling status in My Cloud VOC.
For any further questions, feel free to contact us through the chatbot.
Chatbot