Configuring Auto Scaling for an MRS Cluster

Creating a Cluster and Configuring Task Nodes

• The following steps use a Hadoop analysis cluster of MRS 3.1.0 as an example to describe how to quickly purchase a cluster.
• Only task node groups support auto scaling. Check whether a task node exists in the current cluster before configuring auto scaling.

1. Log in to the Huawei Cloud management console and choose Analytics > MapReduce Service. Click Buy Cluster, configure the parameters on the Quick Config tab page, and click Buy Now.

   Table 1 Parameters (for reference only)

   Parameter	Value
   Region	Select the region based on service requirements.
   Billing Mode	Pay-per-use
   Cluster Name	MRS_demo
   Cluster Version	MRS 3.1.0
   Component	Hadoop Analysis Cluster
   AZ	AZ2
   VPC	vpc-gggg
   Subnet	subnet-64db
   Enterprise Project	default
   Kerberos Authentication	Disabled
   Username	root/admin
   Password	Set the password for logging in to the cluster management page and ECS node, for example, Test!@12345.
   Confirm Password	Enter the password again.
   Secure Communications	Select Enable.

   

2. Click the created cluster and click Nodes to check whether there is a Task node in the cluster.
   • If yes, no further action is required.
   • If no, go to 3.

3. Configure a task node.
   1. On the Nodes page, click Configure Task Node.
      

      For MRS 3.x or later, Configure Task Node applies only to analysis clusters, streaming clusters, and hybrid clusters.

   2. Set required parameters.

      

   3. Click OK.

Scenario 1: Using Auto Scaling Rules Alone

The following is an example of the service scenario:

The number of nodes needs to be dynamically adjusted based on the Yarn resource usage. When the memory available for Yarn is less than 20%, five nodes need to be added. When the memory available for Yarn is greater than 70%, five nodes need to be reduced. The number of nodes in a task node group ranges from 1 to 10.

1. Create a cluster and configure task nodes by referring to Creating a Cluster and Configuring Task Nodes.
2. On the MRS console, choose Clusters > Active Clusters and click the name of the target cluster to access its details page.
3. Click Nodes and click Auto Scaling in the Operation column of the task node group.
4. On the Auto Scaling page, click to enable auto scaling and set Node Range to 1-10.

   

5. Configure scale-out rules.
   1. Select Scale-out in the Auto Scaling Rule area.
   2. Click Add Rule next to Scale-out.
   3. On the Add Rule page, set the related parameters.
      • Rule Name: Retain the default value, for example, default-expand-2.
      • If: Select YARNMemoryAvailablePercentage and Less than from the drop-down lists, and set the percentage to 20% (for details about related metrics, see Table 2).
      • Last For: Set it to 1 five-minute periods.
      • Add: Set it to 5 nodes.
      • Cooldown Period: Set it to 20 minutes.
   4. Click OK.

      

6. Configure scale-in rules.
   1. Select Scale-in in the Auto Scaling Rule area.
   2. Click Add Rule next to Scale-in.
   3. On the Add Rule page, set the related parameters.
      • Rule Name: Retain the default value, for example, default-shrink-2.
      • If: Select YARNMemoryAvailablePercentage and Greater than from the drop-down lists, and set the percentage to 70% (for details about related indicators, see Table 2).
      • Last For: Set it to 1 five-minute periods.
      • Terminate: Set it to 5 nodes.
      • Cooldown Period: Set it to 20 minutes.
   4. Click OK.

      

7. Select I agree to authorize MRS to scale out or in nodes based on the above rule.
8. Click OK.

Scenario 2: Using Resource Plans Alone

The following is an example of the service scenario:

The number of nodes needs to be increased or decreased periodically. 10 nodes are required from 10:00 to 22:00 due to heavy service traffic, and five nodes are required in other time segments.

1. Create a cluster and configure task nodes by referring to Creating a Cluster and Configuring Task Nodes.
2. On the MRS console, choose Clusters > Active Clusters and click the name of the target cluster to access its details page.
3. Click Nodes and click Auto Scaling in the Operation column of the task node group.
4. On the Auto Scaling page, enable auto scaling and configure Node Range.
   • Auto Scaling: Enable.
   • Node Range: 5-5.

5. Click Configure Node Range for Specified Time Range under Default Range and set related parameters.
   • Time Period: 10:00-22:00.
   • Node Range: 10-10.

   

6. Select I agree to authorize MRS to scale out or in nodes based on the above rule.
7. Click OK.

Scenario 3: Using Auto Scaling Rules and Resource Plans Together

The following is an example of configuring both auto scaling rules and resource plans.

The following is an example of the service scenario:

Even though the service data volume for real-time processing changes regularly from 7:00 to 13:00 every day, it is still unstable. Assume that during 7:00 to 13:00, the number of required task nodes ranges from 5 to 8, and in other time ranges, the number of required task nodes ranges from 2 to 4 based on the number of tasks running on Yarn.

1. Create a cluster and configure task nodes by referring to Creating a Cluster and Configuring Task Nodes.
2. On the MRS console, choose Clusters > Active Clusters and click the name of the target cluster to access its details page.
3. Click Nodes and click Auto Scaling in the Operation column of the task node group.
4. On the Auto Scaling page, enable auto scaling, and set Node Range to 2-4.
   Figure 1 Configuring auto scaling
   

5. Configure a resource plan.
   1. Click Configure Node Range for Specific Time Range under Default Range.
   2. Configure the Time Range and Node Range parameters.
      Figure 2 Auto scaling
      

      Time Range: Set it to 07:00-13:00.

      Node Range: Set it to 5-8.

6. Configure an auto scaling rule.
   1. Select Scale-out.
   2. Click Add Rule on the right.
      Figure 3 Adding a rule
      

      Rule Name: default-expand-2.

      If: Select the rule objects and constraints from the drop-down list boxes, for example, YARNAppRunning is greater than 75.

      Last For: Set it to 1 five-minute periods.

      Add: Set it to 1 node.

      Cooldown Period: Set it to 20 minutes.

   3. Click OK.

7. Select I agree to authorize MRS to scale out or in nodes based on the above rule.
8. Click OK.

Reference Information

When adding a rule, you can refer to Table 2 to configure the corresponding metrics.

• Hybrid clusters support all metrics of analysis and streaming clusters.
• The accuracy of different value types in Table 2 is as follows:
  • Integer: integer
  • Percentage: 0.01
  • Ratio: 0.01

Table 2 Auto scaling metrics

Cluster Type	Metric	Value Type	Description
Streaming cluster	StormSlotAvailable	Integer	Number of available Storm slots. Value range: 0 to 2147483646.
	StormSlotAvailablePercentage	Percentage	Percentage of available Storm slots, that is, the proportion of the available slots to total slots. Value range: 0 to 100.
	StormSlotUsed	Integer	Number of used Storm slots. Value range: 0 to 2147483646.
	StormSlotUsedPercentage	Percentage	Percentage of the used Storm slots, that is, the proportion of the used slots to total slots. Value range: 0 to 100.
	StormSupervisorMemAverageUsage	Integer	Average memory usage of the Supervisor process of Storm. Value range: 0 to 2147483646.
	StormSupervisorMemAverageUsagePercentage	Percentage	Average percentage of the used memory of the Supervisor process of Storm to the total memory of the system. Value range: 0 to 100.
	StormSupervisorCPUAverageUsagePercentage	Percentage	Average percentage of the used CPUs of the Supervisor process of Storm to the total CPUs. Value range: 0 to 6,000.
Analysis cluster	YARNAppPending	Integer	Number of pending tasks on Yarn. Value range: 0 to 2147483646.
	YARNAppPendingRatio	Ratio	Ratio of pending tasks on Yarn, that is, the ratio of pending tasks to running tasks on Yarn. Value range: 0 to 2147483646.
	YARNAppRunning	Integer	Number of running tasks on Yarn. Value range: 0 to 2147483646.
	YARNContainerAllocated	Integer	Number of containers allocated to YARN. Value range: 0 to 2147483646.
	YARNContainerPending	Integer	Number of pending containers on Yarn. Value range: 0 to 2147483646.
	YARNContainerPendingRatio	Ratio	Ratio of pending containers on Yarn, that is, the ratio of pending containers to running containers on Yarn. Value range: 0 to 2147483646.
	YARNCPUAllocated	Integer	Number of virtual CPUs (vCPUs) allocated to Yarn. Value range: 0 to 2147483646.
	YARNCPUAvailable	Integer	Number of available vCPUs on Yarn. Value range: 0 to 2147483646.
	YARNCPUAvailablePercentage	Percentage	Percentage of available vCPUs on Yarn, that is, the proportion of available vCPUs to total vCPUs. Value range: 0 to 100.
	YARNCPUPending	Integer	Number of pending vCPUs on Yarn. Value range: 0 to 2147483646.
	YARNMemoryAllocated	Integer	Memory allocated to Yarn. The unit is MB. Value range: 0 to 2147483646.
	YARNMemoryAvailable	Integer	Available memory on Yarn. The unit is MB. Value range: 0 to 2147483646.
	YARNMemoryAvailablePercentage	Percentage	Percentage of available memory on Yarn, that is, the proportion of available memory to total memory on Yarn. Value range: 0 to 100.
	YARNMemoryPending	Integer	Pending memory on Yarn. Value range: 0 to 2147483646.