このページは、お客様の言語ではご利用いただけません。Huawei Cloudは、より多くの言語バージョンを追加するために懸命に取り組んでいます。ご協力ありがとうございました。

Compute
Elastic Cloud Server
Huawei Cloud Flexus
Bare Metal Server
Auto Scaling
Image Management Service
Dedicated Host
FunctionGraph
Cloud Phone Host
Huawei Cloud EulerOS
Networking
Virtual Private Cloud
Elastic IP
Elastic Load Balance
NAT Gateway
Direct Connect
Virtual Private Network
VPC Endpoint
Cloud Connect
Enterprise Router
Enterprise Switch
Global Accelerator
Management & Governance
Cloud Eye
Identity and Access Management
Cloud Trace Service
Resource Formation Service
Tag Management Service
Log Tank Service
Config
OneAccess
Resource Access Manager
Simple Message Notification
Application Performance Management
Application Operations Management
Organizations
Optimization Advisor
IAM Identity Center
Cloud Operations Center
Resource Governance Center
Migration
Server Migration Service
Object Storage Migration Service
Cloud Data Migration
Migration Center
Cloud Ecosystem
KooGallery
Partner Center
User Support
My Account
Billing Center
Cost Center
Resource Center
Enterprise Management
Service Tickets
HUAWEI CLOUD (International) FAQs
ICP Filing
Support Plans
My Credentials
Customer Operation Capabilities
Partner Support Plans
Professional Services
Analytics
MapReduce Service
Data Lake Insight
CloudTable Service
Cloud Search Service
Data Lake Visualization
Data Ingestion Service
GaussDB(DWS)
DataArts Studio
Data Lake Factory
DataArts Lake Formation
IoT
IoT Device Access
Others
Product Pricing Details
System Permissions
Console Quick Start
Common FAQs
Instructions for Associating with a HUAWEI CLOUD Partner
Message Center
Security & Compliance
Security Technologies and Applications
Web Application Firewall
Host Security Service
Cloud Firewall
SecMaster
Anti-DDoS Service
Data Encryption Workshop
Database Security Service
Cloud Bastion Host
Data Security Center
Cloud Certificate Manager
Edge Security
Managed Threat Detection
Blockchain
Blockchain Service
Web3 Node Engine Service
Media Services
Media Processing Center
Video On Demand
Live
SparkRTC
MetaStudio
Storage
Object Storage Service
Elastic Volume Service
Cloud Backup and Recovery
Storage Disaster Recovery Service
Scalable File Service Turbo
Scalable File Service
Volume Backup Service
Cloud Server Backup Service
Data Express Service
Dedicated Distributed Storage Service
Containers
Cloud Container Engine
SoftWare Repository for Container
Application Service Mesh
Ubiquitous Cloud Native Service
Cloud Container Instance
Databases
Relational Database Service
Document Database Service
Data Admin Service
Data Replication Service
GeminiDB
GaussDB
Distributed Database Middleware
Database and Application Migration UGO
TaurusDB
Middleware
Distributed Cache Service
API Gateway
Distributed Message Service for Kafka
Distributed Message Service for RabbitMQ
Distributed Message Service for RocketMQ
Cloud Service Engine
Multi-Site High Availability Service
EventGrid
Dedicated Cloud
Dedicated Computing Cluster
Business Applications
Workspace
ROMA Connect
Message & SMS
Domain Name Service
Edge Data Center Management
Meeting
AI
Face Recognition Service
Graph Engine Service
Content Moderation
Image Recognition
Optical Character Recognition
ModelArts
ImageSearch
Conversational Bot Service
Speech Interaction Service
Huawei HiLens
Video Intelligent Analysis Service
Developer Tools
SDK Developer Guide
API Request Signing Guide
Terraform
Koo Command Line Interface
Content Delivery & Edge Computing
Content Delivery Network
Intelligent EdgeFabric
CloudPond
Intelligent EdgeCloud
Solutions
SAP Cloud
High Performance Computing
Developer Services
ServiceStage
CodeArts
CodeArts PerfTest
CodeArts Req
CodeArts Pipeline
CodeArts Build
CodeArts Deploy
CodeArts Artifact
CodeArts TestPlan
CodeArts Check
CodeArts Repo
Cloud Application Engine
MacroVerse aPaaS
KooMessage
KooPhone
KooDrive
On this page

Adjusting Scaling Policies for Queues in an Elastic Resource Pool

Updated on 2024-12-28 GMT+08:00

Multiple queues can be added to an elastic resource pool. For how to add a queue, see Creating an Elastic Resource Pool and Creating Queues Within It. You can configure the number of CUs you want based on the compute resources used by DLI queues during peaks and troughs and set priorities for the scaling policies to ensure stable running of jobs.

Precautions

  • You are advised to implement fine-grained management of resource pools for stream and batch processing jobs by placing Flink real-time stream jobs and SQL batch processing jobs in separate elastic resource pools.

    Flink real-time stream jobs can run stably without forced scale-in, thus avoiding job interruption and system instability.

    SQL batch processing jobs are placed in independent resource pools, which can scale out and in more flexibly, significantly enhancing the success rate and operational efficiency of scaling operations.

  • 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.
  • 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 periods of scaling policies cannot overlap.
  • The period of a scaling policy can only be set by hour and specified by the start time and end time. For example, if you set the period to 00-09, the time range when the policy takes effect is [00:00, 09:00). The period of the default scaling policy cannot be modified.
  • In any period, compute resources are preferentially allocated to meet the minimum number of CUs of all queues. The remaining CUs (total CUs of the elastic resource pool – total minimum CUs of all queues) are allocated in accordance with the scaling policy priorities.
  • After the queue is scaled out, the system starts billing you for the added CUs. So, if you do not have sufficient requirements, scale in your queue to release unnecessary CUs to save cost.
    Table 1 CU allocation (without jobs)

    Scenario

    CUs

    An elastic resource pool has a maximum number of 256 CUs for queue A and queue B. The scaling policies are as follows:

    • Queue A: priority 5; period: 00:00–09:00; minimum CU: 32; maximum CU: 64
    • Queue B: priority 10; time period: 00:00–09:00; minimum CU: 64; maximum CU: 128

    From 00:00 a.m. to 09:00 a.m.:

    1. The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 160 CUs remaining.
    2. The remaining CUs are allocated based on priority. Since queue B has a higher priority than queue A, 64 CUs will be allocated to queue B first, followed by the allocation of 32 CUs to queue A.

    An elastic resource pool has a maximum number of 96 CUs for queue A and queue B. The scaling policies are as follows:

    • Queue A: priority 5; period: 00:00–09:00; minimum CU: 32; maximum CU: 64
    • Queue B: priority 10; time period: 00:00–09:00; minimum CU: 64; maximum CU: 128

    From 00:00 a.m. to 09:00 a.m.:

    1. The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are no remaining CUs.
    2. The allocation is complete.

    An elastic resource pool has a maximum number of 128 CUs for queue A and queue B. The scaling policies are as follows:

    • Queue A: priority 5; period: 00:00–09:00; minimum CU: 32; maximum CU: 64
    • Queue B: priority 10; time period: 00:00–09:00; minimum CU: 64; maximum CU: 128

    From 00:00 a.m. to 09:00 a.m.:

    1. The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 32 CUs remaining.
    2. The remaining 32 CUs are preferentially allocated to queue B.

    An elastic resource pool has a maximum number of 128 CUs for queue A and queue B. The scaling policies are as follows:

    • Queue A: priority 5; period: 00:00–09:00; minimum CU: 32; maximum CU: 64
    • Queue B: priority 5; time period: 00:00–09:00; minimum CU: 64; maximum CU: 128

    From 00:00 a.m. to 09:00 a.m.:

    1. The minimum CUs are allocated to the two queues. Queue A has 32 CUs, and queue B has 64 CUs. There are 32 CUs remaining.
    2. The two queues have the same priority, the remaining 32 CUs are randomly allocated to the two queues.
    Table 2 CU allocation (with jobs)

    Scenario

    Actual CUs of Elastic Resource Pool

    CUs Allocated to Queue A

    CUs Allocated to Queue B

    Allocation Description

    Queues A and B are added to the elastic resource pool. The scaling policies are as follows:

    • Queue A: period: 00:00–09:00; minimum CU: 32; maximum CU: 64
    • Queue B: period: 00:00–09:00; minimum CU: 64; maximum CU: 128

    192 CUs

    64 CUs

    128 CUs

    If the actual CUs of the elastic resource pool are greater than or equal to the sum of the maximum CUs of the two queues,

    the maximum CUs are allocated to both queues.

    96 CUs

    32 CUs

    64 CUs

    The elastic resource pool preferentially meets the minimum CUs of the two queues.

    After the minimum CUs are allocated to the two queues, no CUs are allocatable.

    128 CUs

    32 CUs to 64 CUs

    64 CUs to 96 CUs

    The elastic resource pool preferentially meets the minimum CUs of the two queues. That is, 32 CUs are allocated to queue A, 64 CUs are allocated to queue B, and the remaining 32 CUs are available.

    The remaining CUs are allocated based on the queue load and priority. The actual CUs of the queue change within the range listed.

Managing Queues

  1. In the navigation pane on the left, choose Resources > Resource Pool.
  2. Locate the target elastic resource pool and click Queue MGMT in the Operation column. The Queue Management page is displayed.
  3. View the queues added to the elastic resource pool.

    Table 3 Queue parameters

    Parameter

    Description

    Name

    Name of the queue to add

    Type

    Queue type

    • For SQL
    • For general purpose

    Period

    The start and end time of the queue scaling policy. This time range includes the start time but not the end time, that is, [start time, end time).

    Min CUs

    Minimum number of CUs allowed by the scaling policy.

    Max CUs

    Maximum number of CUs allowed by the scaling policy.

    Priority

    Priority of the scaling policy for a queue in the elastic resource pool. The priority ranges from 1 to 100. A smaller value indicates a lower priority.

    Engine

    For a queue running SQL jobs, the engine is Spark.

    For a queue for general purpose, the engine can be Spark or Flink, but it is displayed by -- in this page.

    Created

    Time when a queue is added to the elastic resource pool

    Enterprise Project

    Enterprise project the queue belongs to.

    Queues under different enterprise projects can be added to an elastic resource pool.

    Owner

    User who added this queue

    Operation

    • Edit: Modify or add a scaling policy.
    • Delete: Delete the queue.
    Figure 1 Managing queues

  4. Locate the target queue and click Edit in the Operation column.
  5. In the displayed Queue Management pane, perform the following operations as needed:

    Figure 2 Editing scaling policies for a queue
    • Add: Click Create to add a scaling policy. Set Priority, Period, Min CU, and Max CU, and click OK.
    • Modify: Modify parameters of an existing scaling policy and click OK.
    • Delete: Locate the row that contains the scaling policy you want, click Delete and click OK.
      NOTE:

      The Priority and Period parameters must meet the following requirements:

      • Priority: The default value is 1. The value ranges from 1 to 100. A larger value indicates a higher priority.
      • Period:
        • You can only set the period to hours in [start time,end time) format.
        • 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.
      • Max CUs and Min CUs:
        • 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.
        • 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.

  6. After you finish the settings, click statistics icon in the upper right corner of the queue list to view all scaling policies of all queue in the elastic resource pool.

    Figure 3 Viewing statistic graphics
    Figure 4 Statistic graphics of queues and scaling policies

  7. View the scaling task generated when the scaling starts. Go to Job Management > SQL Jobs and view the jobs of the SCALE_QUEUE type.

We use cookies to improve our site and your experience. By continuing to browse our site you accept our cookie policy. Find out more

Feedback

Feedback

Feedback

0/500

Selected Content

Submit selected content with the feedback