配置弹性伸缩规则

package com.huaweicloud.sdk.test;

import com.huaweicloud.sdk.core.auth.ICredential;
import com.huaweicloud.sdk.core.auth.BasicCredentials;
import com.huaweicloud.sdk.core.exception.ConnectionException;
import com.huaweicloud.sdk.core.exception.RequestTimeoutException;
import com.huaweicloud.sdk.core.exception.ServiceResponseException;
import com.huaweicloud.sdk.mrs.v1.region.MrsRegion;
import com.huaweicloud.sdk.mrs.v1.*;
import com.huaweicloud.sdk.mrs.v1.model.*;

import java.util.List;
import java.util.ArrayList;

public class CreateScalingPolicySolution {

    public static void main(String[] args) {
        // The AK and SK used for authentication are hard-coded or stored in plaintext, which has great security risks. It is recommended that the AK and SK be stored in ciphertext in configuration files or environment variables and decrypted during use to ensure security.
        // In this example, AK and SK are stored in environment variables for authentication. Before running this example, set environment variables CLOUD_SDK_AK and CLOUD_SDK_SK in the local environment
        String ak = System.getenv("CLOUD_SDK_AK");
        String sk = System.getenv("CLOUD_SDK_SK");
        String projectId = "{project_id}";

        ICredential auth = new BasicCredentials()
                .withProjectId(projectId)
                .withAk(ak)
                .withSk(sk);

        MrsClient client = MrsClient.newBuilder()
                .withCredential(auth)
                .withRegion(MrsRegion.valueOf("<YOUR REGION>"))
                .build();
        CreateScalingPolicyRequest request = new CreateScalingPolicyRequest();
        request.withClusterId("{cluster_id}");
        AutoScalingPolicyReqV11 body = new AutoScalingPolicyReqV11();
        List<String> listExecScriptsNodes = new ArrayList<>();
        listExecScriptsNodes.add("master_node_default_group");
        listExecScriptsNodes.add("core_node_analysis_group");
        listExecScriptsNodes.add("task_node_analysis_group");
        List<String> listExecScriptsNodes1 = new ArrayList<>();
        listExecScriptsNodes1.add("master_node_default_group");
        listExecScriptsNodes1.add("core_node_analysis_group");
        listExecScriptsNodes1.add("task_node_analysis_group");
        List<ScaleScript> listAutoScalingPolicyExecScripts = new ArrayList<>();
        listAutoScalingPolicyExecScripts.add(
            new ScaleScript()
                .withName("before_scale_out")
                .withUri("s3a://XXX/zeppelin_install.sh")
                .withParameters("${mrs_scale_node_num} ${mrs_scale_type} xxx")
                .withNodes(listExecScriptsNodes1)
                .withActiveMaster(true)
                .withFailAction(ScaleScript.FailActionEnum.fromValue("continue"))
                .withActionStage(ScaleScript.ActionStageEnum.fromValue("before_scale_out"))
        );
        listAutoScalingPolicyExecScripts.add(
            new ScaleScript()
                .withName("after_scale_out")
                .withUri("s3a://XXX/storm_rebalance.sh")
                .withParameters("${mrs_scale_node_hostnames} ${mrs_scale_node_ips}")
                .withNodes(listExecScriptsNodes)
                .withActiveMaster(true)
                .withFailAction(ScaleScript.FailActionEnum.fromValue("continue"))
                .withActionStage(ScaleScript.ActionStageEnum.fromValue("after_scale_out"))
        );
        Trigger triggerRules = new Trigger();
        triggerRules.withMetricName("YARNMemoryAvailablePercentage")
            .withMetricValue("70")
            .withComparisonOperator("GT")
            .withEvaluationPeriods(10);
        Trigger triggerRules1 = new Trigger();
        triggerRules1.withMetricName("YARNMemoryAvailablePercentage")
            .withMetricValue("25")
            .withComparisonOperator("LT")
            .withEvaluationPeriods(10);
        List<Rule> listAutoScalingPolicyRules = new ArrayList<>();
        listAutoScalingPolicyRules.add(
            new Rule()
                .withName("default-expand-1")
                .withAdjustmentType(Rule.AdjustmentTypeEnum.fromValue("scale_out"))
                .withCoolDownMinutes(5)
                .withScalingAdjustment(1)
                .withTrigger(triggerRules1)
        );
        listAutoScalingPolicyRules.add(
            new Rule()
                .withName("default-shrink-1")
                .withAdjustmentType(Rule.AdjustmentTypeEnum.fromValue("scale_in"))
                .withCoolDownMinutes(5)
                .withScalingAdjustment(1)
                .withTrigger(triggerRules)
        );
        List<ResourcesPlan> listAutoScalingPolicyResourcesPlans = new ArrayList<>();
        listAutoScalingPolicyResourcesPlans.add(
            new ResourcesPlan()
                .withPeriodType("daily")
                .withStartTime("9:50")
                .withEndTime("10:20")
                .withMinCapacity(2)
                .withMaxCapacity(3)
        );
        listAutoScalingPolicyResourcesPlans.add(
            new ResourcesPlan()
                .withPeriodType("daily")
                .withStartTime("10:20")
                .withEndTime("12:30")
                .withMinCapacity(0)
                .withMaxCapacity(2)
        );
        AutoScalingPolicy autoScalingPolicybody = new AutoScalingPolicy();
        autoScalingPolicybody.withAutoScalingEnable(true)
            .withMinCapacity(1)
            .withMaxCapacity(3)
            .withResourcesPlans(listAutoScalingPolicyResourcesPlans)
            .withRules(listAutoScalingPolicyRules)
            .withExecScripts(listAutoScalingPolicyExecScripts);
        body.withAutoScalingPolicy(autoScalingPolicybody);
        body.withNodeGroup(AutoScalingPolicyReqV11.NodeGroupEnum.fromValue("task_node_analysis_group"));
        request.withBody(body);
        try {
            CreateScalingPolicyResponse response = client.createScalingPolicy(request);
            System.out.println(response.toString());
        } catch (ConnectionException e) {
            e.printStackTrace();
        } catch (RequestTimeoutException e) {
            e.printStackTrace();
        } catch (ServiceResponseException e) {
            e.printStackTrace();
            System.out.println(e.getHttpStatusCode());
            System.out.println(e.getRequestId());
            System.out.println(e.getErrorCode());
            System.out.println(e.getErrorMsg());
        }
    }
}

# coding: utf-8

import os
from huaweicloudsdkcore.auth.credentials import BasicCredentials
from huaweicloudsdkmrs.v1.region.mrs_region import MrsRegion
from huaweicloudsdkcore.exceptions import exceptions
from huaweicloudsdkmrs.v1 import *

if __name__ == "__main__":
    # The AK and SK used for authentication are hard-coded or stored in plaintext, which has great security risks. It is recommended that the AK and SK be stored in ciphertext in configuration files or environment variables and decrypted during use to ensure security.
    # In this example, AK and SK are stored in environment variables for authentication. Before running this example, set environment variables CLOUD_SDK_AK and CLOUD_SDK_SK in the local environment
    ak = os.environ["CLOUD_SDK_AK"]
    sk = os.environ["CLOUD_SDK_SK"]
    projectId = "{project_id}"

    credentials = BasicCredentials(ak, sk, projectId)

    client = MrsClient.new_builder() \
        .with_credentials(credentials) \
        .with_region(MrsRegion.value_of("<YOUR REGION>")) \
        .build()

    try:
        request = CreateScalingPolicyRequest()
        request.cluster_id = "{cluster_id}"
        listNodesExecScripts = [
            "master_node_default_group",
            "core_node_analysis_group",
            "task_node_analysis_group"
        ]
        listNodesExecScripts1 = [
            "master_node_default_group",
            "core_node_analysis_group",
            "task_node_analysis_group"
        ]
        listExecScriptsAutoScalingPolicy = [
            ScaleScript(
                name="before_scale_out",
                uri="s3a://XXX/zeppelin_install.sh",
                parameters="${mrs_scale_node_num} ${mrs_scale_type} xxx",
                nodes=listNodesExecScripts1,
                active_master=True,
                fail_action="continue",
                action_stage="before_scale_out"
            ),
            ScaleScript(
                name="after_scale_out",
                uri="s3a://XXX/storm_rebalance.sh",
                parameters="${mrs_scale_node_hostnames} ${mrs_scale_node_ips}",
                nodes=listNodesExecScripts,
                active_master=True,
                fail_action="continue",
                action_stage="after_scale_out"
            )
        ]
        triggerRules = Trigger(
            metric_name="YARNMemoryAvailablePercentage",
            metric_value="70",
            comparison_operator="GT",
            evaluation_periods=10
        )
        triggerRules1 = Trigger(
            metric_name="YARNMemoryAvailablePercentage",
            metric_value="25",
            comparison_operator="LT",
            evaluation_periods=10
        )
        listRulesAutoScalingPolicy = [
            Rule(
                name="default-expand-1",
                adjustment_type="scale_out",
                cool_down_minutes=5,
                scaling_adjustment=1,
                trigger=triggerRules1
            ),
            Rule(
                name="default-shrink-1",
                adjustment_type="scale_in",
                cool_down_minutes=5,
                scaling_adjustment=1,
                trigger=triggerRules
            )
        ]
        listResourcesPlansAutoScalingPolicy = [
            ResourcesPlan(
                period_type="daily",
                start_time="9:50",
                end_time="10:20",
                min_capacity=2,
                max_capacity=3
            ),
            ResourcesPlan(
                period_type="daily",
                start_time="10:20",
                end_time="12:30",
                min_capacity=0,
                max_capacity=2
            )
        ]
        autoScalingPolicybody = AutoScalingPolicy(
            auto_scaling_enable=True,
            min_capacity=1,
            max_capacity=3,
            resources_plans=listResourcesPlansAutoScalingPolicy,
            rules=listRulesAutoScalingPolicy,
            exec_scripts=listExecScriptsAutoScalingPolicy
        )
        request.body = AutoScalingPolicyReqV11(
            auto_scaling_policy=autoScalingPolicybody,
            node_group="task_node_analysis_group"
        )
        response = client.create_scaling_policy(request)
        print(response)
    except exceptions.ClientRequestException as e:
        print(e.status_code)
        print(e.request_id)
        print(e.error_code)
        print(e.error_msg)

package main

import (
	"fmt"
	"github.com/huaweicloud/huaweicloud-sdk-go-v3/core/auth/basic"
    mrs "github.com/huaweicloud/huaweicloud-sdk-go-v3/services/mrs/v1"
	"github.com/huaweicloud/huaweicloud-sdk-go-v3/services/mrs/v1/model"
    region "github.com/huaweicloud/huaweicloud-sdk-go-v3/services/mrs/v1/region"
)

func main() {
    // The AK and SK used for authentication are hard-coded or stored in plaintext, which has great security risks. It is recommended that the AK and SK be stored in ciphertext in configuration files or environment variables and decrypted during use to ensure security.
    // In this example, AK and SK are stored in environment variables for authentication. Before running this example, set environment variables CLOUD_SDK_AK and CLOUD_SDK_SK in the local environment
    ak := os.Getenv("CLOUD_SDK_AK")
    sk := os.Getenv("CLOUD_SDK_SK")
    projectId := "{project_id}"

    auth := basic.NewCredentialsBuilder().
        WithAk(ak).
        WithSk(sk).
        WithProjectId(projectId).
        Build()

    client := mrs.NewMrsClient(
        mrs.MrsClientBuilder().
            WithRegion(region.ValueOf("<YOUR REGION>")).
            WithCredential(auth).
            Build())

    request := &model.CreateScalingPolicyRequest{}
	request.ClusterId = "{cluster_id}"
	var listNodesExecScripts = []string{
        "master_node_default_group",
	    "core_node_analysis_group",
	    "task_node_analysis_group",
    }
	var listNodesExecScripts1 = []string{
        "master_node_default_group",
	    "core_node_analysis_group",
	    "task_node_analysis_group",
    }
	parametersExecScripts:= "${mrs_scale_node_num} ${mrs_scale_type} xxx"
	activeMasterExecScripts:= true
	parametersExecScripts1:= "${mrs_scale_node_hostnames} ${mrs_scale_node_ips}"
	activeMasterExecScripts1:= true
	var listExecScriptsAutoScalingPolicy = []model.ScaleScript{
        {
            Name: "before_scale_out",
            Uri: "s3a://XXX/zeppelin_install.sh",
            Parameters: &parametersExecScripts,
            Nodes: listNodesExecScripts1,
            ActiveMaster: &activeMasterExecScripts,
            FailAction: model.GetScaleScriptFailActionEnum().CONTINUE,
            ActionStage: model.GetScaleScriptActionStageEnum().BEFORE_SCALE_OUT,
        },
        {
            Name: "after_scale_out",
            Uri: "s3a://XXX/storm_rebalance.sh",
            Parameters: &parametersExecScripts1,
            Nodes: listNodesExecScripts,
            ActiveMaster: &activeMasterExecScripts1,
            FailAction: model.GetScaleScriptFailActionEnum().CONTINUE,
            ActionStage: model.GetScaleScriptActionStageEnum().AFTER_SCALE_OUT,
        },
    }
	comparisonOperatorTrigger:= "GT"
	triggerRules := &model.Trigger{
		MetricName: "YARNMemoryAvailablePercentage",
		MetricValue: "70",
		ComparisonOperator: &comparisonOperatorTrigger,
		EvaluationPeriods: int32(10),
	}
	comparisonOperatorTrigger1:= "LT"
	triggerRules1 := &model.Trigger{
		MetricName: "YARNMemoryAvailablePercentage",
		MetricValue: "25",
		ComparisonOperator: &comparisonOperatorTrigger1,
		EvaluationPeriods: int32(10),
	}
	var listRulesAutoScalingPolicy = []model.Rule{
        {
            Name: "default-expand-1",
            AdjustmentType: model.GetRuleAdjustmentTypeEnum().SCALE_OUT,
            CoolDownMinutes: int32(5),
            ScalingAdjustment: int32(1),
            Trigger: triggerRules1,
        },
        {
            Name: "default-shrink-1",
            AdjustmentType: model.GetRuleAdjustmentTypeEnum().SCALE_IN,
            CoolDownMinutes: int32(5),
            ScalingAdjustment: int32(1),
            Trigger: triggerRules,
        },
    }
	var listResourcesPlansAutoScalingPolicy = []model.ResourcesPlan{
        {
            PeriodType: "daily",
            StartTime: "9:50",
            EndTime: "10:20",
            MinCapacity: int32(2),
            MaxCapacity: int32(3),
        },
        {
            PeriodType: "daily",
            StartTime: "10:20",
            EndTime: "12:30",
            MinCapacity: int32(0),
            MaxCapacity: int32(2),
        },
    }
	autoScalingPolicybody := &model.AutoScalingPolicy{
		AutoScalingEnable: true,
		MinCapacity: int32(1),
		MaxCapacity: int32(3),
		ResourcesPlans: &listResourcesPlansAutoScalingPolicy,
		Rules: &listRulesAutoScalingPolicy,
		ExecScripts: &listExecScriptsAutoScalingPolicy,
	}
	request.Body = &model.AutoScalingPolicyReqV11{
		AutoScalingPolicy: autoScalingPolicybody,
		NodeGroup: model.GetAutoScalingPolicyReqV11NodeGroupEnum().TASK_NODE_ANALYSIS_GROUP,
	}
	response, err := client.CreateScalingPolicy(request)
	if err == nil {
        fmt.Printf("%+v\n", response)
    } else {
        fmt.Println(err)
    }
}