Cloud 클라이언트 라이브러리를 사용하여 워크플로 실행

이 빠른 시작에서는 Cloud 클라이언트 라이브러리를 사용하여 워크플로를 실행하고 실행 결과를 확인하는 방법을 보여줍니다.

Cloud 클라이언트 라이브러리 설치 및 개발 환경 설정에 관한 자세한 내용은 Workflows 클라이언트 라이브러리 개요를 참고하세요.

터미널이나 Cloud Shell에서 Google Cloud CLI를 사용하여 다음 단계를 완료할 수 있습니다.

시작하기 전에

조직에서 정의한 보안 제약조건으로 인해 다음 단계를 완료하지 못할 수 있습니다. 문제 해결 정보는 제한된 Google Cloud 환경에서 애플리케이션 개발을 참조하세요.

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. Install the Google Cloud CLI.
  3. To initialize the gcloud CLI, run the following command:

    gcloud init
  4. Create or select a Google Cloud project.

    • Create a Google Cloud project:

      gcloud projects create PROJECT_ID

      Replace PROJECT_ID with a name for the Google Cloud project you are creating.

    • Select the Google Cloud project that you created:

      gcloud config set project PROJECT_ID

      Replace PROJECT_ID with your Google Cloud project name.

  5. Make sure that billing is enabled for your Google Cloud project.

  6. Enable the Workflows API:

    gcloud services enable workflows.googleapis.com
  7. Set up authentication:

    1. Create the service account:

      gcloud iam service-accounts create SERVICE_ACCOUNT_NAME

      Replace SERVICE_ACCOUNT_NAME with a name for the service account.

    2. Grant the roles/owner IAM role to the service account:

      gcloud projects add-iam-policy-binding PROJECT_ID --member="serviceAccount:SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com" --role=roles/owner

      Replace the following:

      • SERVICE_ACCOUNT_NAME: the name of the service account
      • PROJECT_ID: the project ID where you created the service account
  8. Install the Google Cloud CLI.
  9. To initialize the gcloud CLI, run the following command:

    gcloud init
  10. Create or select a Google Cloud project.

    • Create a Google Cloud project:

      gcloud projects create PROJECT_ID

      Replace PROJECT_ID with a name for the Google Cloud project you are creating.

    • Select the Google Cloud project that you created:

      gcloud config set project PROJECT_ID

      Replace PROJECT_ID with your Google Cloud project name.

  11. Make sure that billing is enabled for your Google Cloud project.

  12. Enable the Workflows API:

    gcloud services enable workflows.googleapis.com
  13. Set up authentication:

    1. Create the service account:

      gcloud iam service-accounts create SERVICE_ACCOUNT_NAME

      Replace SERVICE_ACCOUNT_NAME with a name for the service account.

    2. Grant the roles/owner IAM role to the service account:

      gcloud projects add-iam-policy-binding PROJECT_ID --member="serviceAccount:SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com" --role=roles/owner

      Replace the following:

      • SERVICE_ACCOUNT_NAME: the name of the service account
      • PROJECT_ID: the project ID where you created the service account
  14. (선택사항) 로그를 Cloud Logging으로 전송하려면 서비스 계정에 roles/logging.logWriter 역할을 부여합니다.

    gcloud projects add-iam-policy-binding PROJECT_ID \
        --member "serviceAccount:SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com" \
        --role "roles/logging.logWriter"

    서비스 계정 역할 및 권한에 대한 자세한 내용은 Google Cloud 리소스에 액세스할 수 있도록 워크플로 권한 부여를 참고하세요.

  15. 필요한 경우 Git 소스 코드 관리 도구를 다운로드하여 설치합니다.

샘플 워크플로 배포

워크플로를 정의한 후 실행에 사용할 수 있도록 워크플로를 배포합니다. 또한 배포 단계 중 소스 파일을 실행할 수 있는지 확인합니다.

다음 워크플로는 요청을 공개 API에 전송한 후 API의 응답을 반환합니다.

  1. 다음 콘텐츠가 포함된 파일 이름이 myFirstWorkflow.yaml인 텍스트 파일을 만듭니다.

    # This workflow accepts an optional "searchTerm" argument for the Wikipedia API.
    # If no input arguments are provided or "searchTerm" is absent,
    # it will fetch the day of the week in Amsterdam and use it as the search term.
    
    main:
        params: [input]
        steps:
        - validateSearchTermAndRedirectToReadWikipedia:
            switch:
                - condition: '${map.get(input, "searchTerm") != null}'
                  assign:
                    - searchTerm: '${input.searchTerm}'
                  next: readWikipedia
        - getCurrentTime:
            call: http.get
            args:
                url: https://timeapi.io/api/Time/current/zone?timeZone=Europe/Amsterdam
            result: currentTime
        - setFromCallResult:
            assign:
                - searchTerm: '${currentTime.body.dayOfWeek}'
        - readWikipedia:
            call: http.get
            args:
                url: 'https://en.wikipedia.org/w/api.php'
                query:
                    action: opensearch
                    search: '${searchTerm}'
            result: wikiResult
        - returnOutput:
                return: '${wikiResult.body[1]}'
  2. 워크플로를 만든 후 배포해도 되지만 워크플로를 실행하지는 마세요.

    gcloud workflows deploy myFirstWorkflow \
        --source=myFirstWorkflow.yaml \
        --service-account=SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com \
        --location=CLOUD_REGION

    CLOUD_REGION을 워크플로의 지원되는 위치로 바꿉니다. 코드 샘플에 사용된 기본 지역은 us-central1입니다.

샘플 코드 가져오기

GitHub에서 샘플 코드를 클론할 수 있습니다.

  1. 샘플 앱 저장소를 로컬 머신에 클론합니다.

    C#

    git clone https://github.com/GoogleCloudPlatform/dotnet-docs-samples.git

    또는 zip 파일로 샘플을 다운로드하고 압축을 풀 수 있습니다.

    Go

    git clone https://github.com/GoogleCloudPlatform/golang-samples.git

    또는 zip 파일로 샘플을 다운로드하고 압축을 풀 수 있습니다.

    자바

    git clone https://github.com/GoogleCloudPlatform/java-docs-samples.git

    또는 zip 파일로 샘플을 다운로드하고 압축을 풀 수 있습니다.

    Node.js

    git clone https://github.com/GoogleCloudPlatform/nodejs-docs-samples.git

    또는 zip 파일로 샘플을 다운로드하고 압축을 풀 수 있습니다.

    Python

    git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git

    또는 zip 파일로 샘플을 다운로드하고 압축을 풀 수 있습니다.

  2. Workflows 샘플 코드가 포함된 디렉터리로 변경합니다.

    C#

    cd dotnet-docs-samples/workflows/api/Workflow.Samples/

    Go

    cd golang-samples/workflows/executions/

    자바

    cd java-docs-samples/workflows/cloud-client/

    Node.js

    cd nodejs-docs-samples/workflows/quickstart/

    Python

    cd python-docs-samples/workflows/cloud-client/

  3. 다음 샘플 코드를 살펴봅니다. 각 샘플 앱은 다음을 실행합니다.

    1. Workflows용 클라우드 클라이언트 라이브러리를 설정합니다.
    2. 워크플로를 실행합니다.
    3. 실행이 종료될 때까지 워크플로 실행을 폴링합니다(지수 백오프 사용).
    4. 실행 결과를 출력합니다.

    C#

    
    using Google.Cloud.Workflows.Common.V1;
    using Google.Cloud.Workflows.Executions.V1;
    using System;
    using System.Threading;
    using System.Threading.Tasks;
    
    public class ExecuteWorkflowSample
    {
        /// <summary>
        /// Execute a workflow and return the execution operation.
        /// </summary>
        /// <param name="projectID">Your Google Cloud Project ID.</param>
        /// <param name="locationID">The region where your workflow is located.</param>
        /// <param name="workflowID">Your Workflow ID.</param>
        /// <returns>
        /// An Execute object representing the completed workflow execution.
        /// </returns>
        public async Task<Execution> ExecuteWorkflow(
            string projectId = "YOUR-PROJECT-ID",
            string locationID = "YOUR-LOCATION-ID",
            string workflowID = "YOUR-WORKFLOW-ID")
        {
            // Initialize the client.
            ExecutionsClient client = await ExecutionsClient.CreateAsync();
    
            // Build the parent location path.
            WorkflowName parent = new WorkflowName(projectId, locationID, workflowID);
    
            // Create an execution request.
            CreateExecutionRequest createExecutionRequest = new CreateExecutionRequest
            {
                ParentAsWorkflowName = parent,
            };
    
            // Execute the operation.
            Execution execution = await client.CreateExecutionAsync(createExecutionRequest);
            Console.WriteLine("- Execution started...");
    
            TimeSpan backoffDelay = TimeSpan.FromSeconds(1);
            TimeSpan maxBackoffDelay = TimeSpan.FromSeconds(16);
    
            // Keep polling the state until the execution finishes, using exponential backoff.
            while (execution.State == Execution.Types.State.Active)
            {
                await Task.Delay(backoffDelay);
    
                // Implement exponential backoff by doubling the delay, but limiting it to a practical duration.
                backoffDelay = (backoffDelay < maxBackoffDelay) ? backoffDelay * 2 : maxBackoffDelay;
    
                execution = await client.GetExecutionAsync(execution.Name);
            }
    
            // Print results.
            Console.WriteLine($"Execution finished with state: {execution.State}");
            Console.WriteLine($"Execution results: {execution.Result}");
    
            // Return the fetched execution.
            return execution;
        }
    }

    Go

    import (
    	"context"
    	"fmt"
    	"io"
    	"time"
    
    	workflowexecutions "google.golang.org/api/workflowexecutions/v1"
    )
    
    // Execute a workflow and print the execution results.
    //
    // For more information about Workflows see:
    // https://cloud.google.com/workflows/docs/overview
    func executeWorkflow(w io.Writer, projectID, workflowID, locationID string) error {
    	// TODO(developer): Uncomment and update the following lines:
    	// projectID := "YOUR_PROJECT_ID"
    	// workflowID := "YOUR_WORKFLOW_ID"
    	// locationID := "YOUR_LOCATION_ID"
    
    	ctx := context.Background()
    
    	// Construct the location path.
    	parent := fmt.Sprintf("projects/%s/locations/%s/workflows/%s", projectID, locationID, workflowID)
    
    	// Create execution client.
    	client, err := workflowexecutions.NewService(ctx)
    	if err != nil {
    		return fmt.Errorf("workflowexecutions.NewService error: %w", err)
    	}
    
    	// Get execution service.
    	service := client.Projects.Locations.Workflows.Executions
    
    	// Build and run the new workflow execution.
    	res, err := service.Create(parent, &workflowexecutions.Execution{}).Do()
    	if err != nil {
    		return fmt.Errorf("service.Create.Do error: %w", err)
    	}
    	fmt.Fprintln(w, "- Execution started...")
    
    	// Set initial value for backoff delay in one second.
    	backoffDelay := time.Second
    
    	for res.State == "ACTIVE" {
    		time.Sleep(backoffDelay)
    
    		// Request the updated state for the execution.
    		getReq := service.Get(res.Name)
    		res, err = getReq.Do()
    		if err != nil {
    			return fmt.Errorf("getReq error: %w", err)
    		}
    
    		// Double the delay to provide exponential backoff (capped at 16 seconds).
    		if backoffDelay < time.Second*16 {
    			backoffDelay *= 2
    		}
    	}
    
    	fmt.Fprintf(w, "Execution finished with state: %s\n", res.State)
    	fmt.Fprintf(w, "Execution results: %s\n", res.Result)
    
    	return nil
    }
    

    Java

    // Imports the Google Cloud client library
    
    import com.google.cloud.workflows.executions.v1.CreateExecutionRequest;
    import com.google.cloud.workflows.executions.v1.Execution;
    import com.google.cloud.workflows.executions.v1.ExecutionsClient;
    import com.google.cloud.workflows.executions.v1.WorkflowName;
    import java.io.IOException;
    import java.util.concurrent.ExecutionException;
    
    public class WorkflowsQuickstart {
    
      private static final String PROJECT = System.getenv("GOOGLE_CLOUD_PROJECT");
      private static final String LOCATION = System.getenv().getOrDefault("LOCATION", "us-central1");
      private static final String WORKFLOW =
          System.getenv().getOrDefault("WORKFLOW", "myFirstWorkflow");
    
      public static void main(String... args)
          throws IOException, InterruptedException, ExecutionException {
        if (PROJECT == null) {
          throw new IllegalArgumentException(
              "Environment variable 'GOOGLE_CLOUD_PROJECT' is required to run this quickstart.");
        }
        workflowsQuickstart(PROJECT, LOCATION, WORKFLOW);
      }
    
      private static volatile boolean finished;
    
      public static void workflowsQuickstart(String projectId, String location, String workflow)
          throws IOException, InterruptedException, ExecutionException {
        // Initialize client that will be used to send requests. This client only needs
        // to be created once, and can be reused for multiple requests. After completing all of your
        // requests, call the "close" method on the client to safely clean up any remaining background
        // resources.
        try (ExecutionsClient executionsClient = ExecutionsClient.create()) {
          // Construct the fully qualified location path.
          WorkflowName parent = WorkflowName.of(projectId, location, workflow);
    
          // Creates the execution object.
          CreateExecutionRequest request =
              CreateExecutionRequest.newBuilder()
                  .setParent(parent.toString())
                  .setExecution(Execution.newBuilder().build())
                  .build();
          Execution response = executionsClient.createExecution(request);
    
          String executionName = response.getName();
          System.out.printf("Created execution: %s%n", executionName);
    
          long backoffTime = 0;
          long backoffDelay = 1_000; // Start wait with delay of 1,000 ms
          final long backoffTimeout = 10 * 60 * 1_000; // Time out at 10 minutes
          System.out.println("Poll for results...");
    
          // Wait for execution to finish, then print results.
          while (!finished && backoffTime < backoffTimeout) {
            Execution execution = executionsClient.getExecution(executionName);
            finished = execution.getState() != Execution.State.ACTIVE;
    
            // If we haven't seen the results yet, wait.
            if (!finished) {
              System.out.println("- Waiting for results");
              Thread.sleep(backoffDelay);
              backoffTime += backoffDelay;
              backoffDelay *= 2; // Double the delay to provide exponential backoff.
            } else {
              System.out.println("Execution finished with state: " + execution.getState().name());
              System.out.println("Execution results: " + execution.getResult());
            }
          }
        }
      }
    }

    Node.js

    const {ExecutionsClient} = require('@google-cloud/workflows');
    const client = new ExecutionsClient();
    /**
     * TODO(developer): Uncomment these variables before running the sample.
     */
    // const projectId = 'my-project';
    // const location = 'us-central1';
    // const workflow = 'myFirstWorkflow';
    // const searchTerm = '';
    
    /**
     * Executes a Workflow and waits for the results with exponential backoff.
     * @param {string} projectId The Google Cloud Project containing the workflow
     * @param {string} location The workflow location
     * @param {string} workflow The workflow name
     * @param {string} searchTerm Optional search term to pass to the Workflow as a runtime argument
     */
    async function executeWorkflow(projectId, location, workflow, searchTerm) {
      /**
       * Sleeps the process N number of milliseconds.
       * @param {Number} ms The number of milliseconds to sleep.
       */
      function sleep(ms) {
        return new Promise(resolve => {
          setTimeout(resolve, ms);
        });
      }
      const runtimeArgs = searchTerm ? {searchTerm: searchTerm} : {};
      // Execute workflow
      try {
        const createExecutionRes = await client.createExecution({
          parent: client.workflowPath(projectId, location, workflow),
          execution: {
            // Runtime arguments can be passed as a JSON string
            argument: JSON.stringify(runtimeArgs),
          },
        });
        const executionName = createExecutionRes[0].name;
        console.log(`Created execution: ${executionName}`);
    
        // Wait for execution to finish, then print results.
        let executionFinished = false;
        let backoffDelay = 1000; // Start wait with delay of 1,000 ms
        console.log('Poll every second for result...');
        while (!executionFinished) {
          const [execution] = await client.getExecution({
            name: executionName,
          });
          executionFinished = execution.state !== 'ACTIVE';
    
          // If we haven't seen the result yet, wait a second.
          if (!executionFinished) {
            console.log('- Waiting for results...');
            await sleep(backoffDelay);
            backoffDelay *= 2; // Double the delay to provide exponential backoff.
          } else {
            console.log(`Execution finished with state: ${execution.state}`);
            console.log(execution.result);
            return execution.result;
          }
        }
      } catch (e) {
        console.error(`Error executing workflow: ${e}`);
      }
    }
    
    executeWorkflow(projectId, location, workflowName, searchTerm).catch(err => {
      console.error(err.message);
      process.exitCode = 1;
    });
    

    Python

    import time
    
    from google.cloud import workflows_v1
    from google.cloud.workflows import executions_v1
    
    from google.cloud.workflows.executions_v1.types import executions
    
    # TODO(developer): Update and uncomment the following lines.
    # project_id = "YOUR_PROJECT_ID"
    # location = "YOUR_LOCATION"  # For example: us-central1
    # workflow_id = "YOUR_WORKFLOW_ID"  # For example: myFirstWorkflow
    
    # Initialize API clients.
    execution_client = executions_v1.ExecutionsClient()
    workflows_client = workflows_v1.WorkflowsClient()
    
    # Construct the fully qualified location path.
    parent = workflows_client.workflow_path(project_id, location, workflow_id)
    
    # Execute the workflow.
    response = execution_client.create_execution(request={"parent": parent})
    print(f"Created execution: {response.name}")
    
    # Wait for execution to finish, then print results.
    execution_finished = False
    backoff_delay = 1  # Start wait with delay of 1 second.
    print("Poll for result...")
    
    # Keep polling the state until the execution finishes,
    # using exponential backoff.
    while not execution_finished:
        execution = execution_client.get_execution(
            request={"name": response.name}
        )
        execution_finished = execution.state != executions.Execution.State.ACTIVE
    
        # If we haven't seen the result yet, keep waiting.
        if not execution_finished:
            print("- Waiting for results...")
            time.sleep(backoff_delay)
            # Double the delay to provide exponential backoff.
            backoff_delay *= 2
        else:
            print(f"Execution finished with state: {execution.state.name}")
            print(f"Execution results: {execution.result}")

샘플 코드 실행

샘플 코드를 실행하고 워크플로를 실행할 수 있습니다. 워크플로를 실행하면 워크플로와 연결된 배포된 워크플로 정의가 실행됩니다.

  1. 샘플을 실행하려면 먼저 종속 항목을 설치합니다.

    C#

    dotnet restore

    Go

    go mod download

    자바

    mvn compile

    Node.js

    npm install -D tsx

    Python

    pip3 install -r requirements.txt

  2. 스크립트를 실행합니다.

    C#

    GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME dotnet run

    Go

    GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME go run .

    자바

    GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME mvn compile exec:java -Dexec.mainClass=com.example.workflows.WorkflowsQuickstart

    Node.js

    npx tsx index.js

    Python

    GOOGLE_CLOUD_PROJECT=PROJECT_ID LOCATION=CLOUD_REGION WORKFLOW=WORKFLOW_NAME python3 main.py

    다음을 바꿉니다.

    • PROJECT_ID: Google Cloud 프로젝트 이름
    • CLOUD_REGION: 워크플로의 위치 (기본값: us-central1)
    • WORKFLOW_NAME: 워크플로 이름 (기본값: myFirstWorkflow)

    출력은 다음과 비슷합니다.

    Execution finished with state: SUCCEEDED
    Execution results: ["Thursday","Thursday Night Football","Thursday (band)","Thursday Island","Thursday (album)","Thursday Next","Thursday at the Square","Thursday's Child (David Bowie song)","Thursday Afternoon","Thursday (film)"]
    

실행 요청에서 데이터 전달

클라이언트 라이브러리 언어에 따라 실행 요청에서 런타임 인수를 전달할 수도 있습니다. 예를 들면 다음과 같습니다.

C#


public class ExecuteWorkflowWithArgumentsSample
{
    /// <summary>
    /// Execute a workflow with arguments and return the execution operation.
    /// </summary>
    /// <param name="projectID">Your Google Cloud Project ID.</param>
    /// <param name="locationID">The region where your workflow is located.</param>
    /// <param name="workflowID">Your Workflow ID.</param>
    /// <returns>
    /// An Execute object representing the completed workflow execution.
    /// </returns>
    public async Task<Execution> ExecuteWorkflowWithArguments(
        string projectId = "YOUR-PROJECT-ID",
        string locationID = "YOUR-LOCATION-ID",
        string workflowID = "YOUR-WORKFLOW-ID")
    {
        // Initialize the client.
        ExecutionsClient client = await ExecutionsClient.CreateAsync();

        // Build the parent location path.
        WorkflowName parent = new WorkflowName(projectId, locationID, workflowID);

        // Serialize the argument.
        string argument = JsonSerializer.Serialize(new
        {
            searchTerm = "Cloud"
        });

        // Create an execution request.
        CreateExecutionRequest createExecutionRequest = new CreateExecutionRequest
        {
            ParentAsWorkflowName = parent,
            Execution = new Execution
            {
                Argument = argument,
            }
        };

        // Execute the operation and recieve the execution.
        Execution execution = await client.CreateExecutionAsync(createExecutionRequest);
        Console.WriteLine("- Execution started...");

        TimeSpan backoffDelay = TimeSpan.FromSeconds(1);
        TimeSpan maxBackoffDelay = TimeSpan.FromSeconds(16);

        // Keep polling the state until the execution finishes, using exponential backoff.
        while (execution.State == Execution.Types.State.Active)
        {
            await Task.Delay(backoffDelay);

            // Implement exponential backoff by doubling the delay, but limiting it to a practical duration.
            backoffDelay = (backoffDelay < maxBackoffDelay) ? backoffDelay * 2 : maxBackoffDelay;

            execution = await client.GetExecutionAsync(execution.Name);
        }

        // Print results.
        Console.WriteLine($"Execution finished with state: {execution.State}");
        Console.WriteLine($"Execution results: {execution.Result}");

        // Return the fetched execution.
        return execution;
    }
}

Go

import (
	"context"
	"encoding/json"
	"fmt"
	"io"
	"time"

	workflowexecutions "google.golang.org/api/workflowexecutions/v1"
)

// Execute a workflow with arguments and print the execution results.
//
// For more information about Workflows see:
// https://cloud.google.com/workflows/docs/overview
func executeWorkflowWithArguments(w io.Writer, projectID, workflowID, locationID string) error {
	// TODO(developer): Uncomment and update the following lines:
	// projectID := "YOUR_PROJECT_ID"
	// workflowID := "YOUR_WORKFLOW_ID"
	// locationID := "YOUR_LOCATION_ID"

	ctx := context.Background()

	// Construct the location path.
	parent := fmt.Sprintf("projects/%s/locations/%s/workflows/%s", projectID, locationID, workflowID)

	// Create execution client.
	client, err := workflowexecutions.NewService(ctx)
	if err != nil {
		return fmt.Errorf("workflowexecutions.NewService error: %w", err)
	}

	// Get execution service.
	service := client.Projects.Locations.Workflows.Executions

	// Create argument.
	argument := struct {
		SearchTerm string `json:"searchTerm"`
	}{
		SearchTerm: "Cloud",
	}

	// Encode argument to JSON.
	argumentEncoded, err := json.Marshal(argument)
	if err != nil {
		return fmt.Errorf("json.Marshal error: %w", err)
	}

	// Build and run the new workflow execution adding the argument.
	res, err := service.Create(parent, &workflowexecutions.Execution{
		Argument: string(argumentEncoded),
	}).Do()
	if err != nil {
		return fmt.Errorf("service.Create.Do error: %w", err)
	}
	fmt.Fprintln(w, "- Execution started...")

	// Set initial value for backoff delay in one second.
	backoffDelay := time.Second

	for res.State == "ACTIVE" {
		time.Sleep(backoffDelay)

		// Request the updated state for the execution.
		getReq := service.Get(res.Name)
		res, err = getReq.Do()
		if err != nil {
			return fmt.Errorf("getReq error: %w", err)
		}

		// Double the delay to provide exponential backoff (capped at 16 seconds).
		if backoffDelay < time.Second*16 {
			backoffDelay *= 2
		}
	}

	fmt.Fprintf(w, "Execution finished with state: %s\n", res.State)
	fmt.Fprintf(w, "Execution arguments: %s", res.Argument)
	fmt.Fprintf(w, "Execution results: %s\n", res.Result)

	return nil
}

Java

// Creates the execution object
CreateExecutionRequest request =
    CreateExecutionRequest.newBuilder()
        .setParent(parent.toString())
        .setExecution(Execution.newBuilder().setArgument("{\"searchTerm\":\"Friday\"}").build())
        .build();

Node.js

// Execute workflow
try {
  const createExecutionRes = await client.createExecution({
    parent: client.workflowPath(projectId, location, workflow),
    execution: {
      argument: JSON.stringify({"searchTerm": "Friday"})
    }
});
const executionName = createExecutionRes[0].name;

Python

import time

from google.cloud import workflows_v1
from google.cloud.workflows import executions_v1

from google.cloud.workflows.executions_v1.types import executions

# TODO(developer): Update and uncomment the following lines.
# project_id = "YOUR_PROJECT_ID"
# location = "YOUR_LOCATION"  # For example: us-central1
# workflow_id = "YOUR_WORKFLOW_ID"  # For example: myFirstWorkflow

# Initialize API clients.
execution_client = executions_v1.ExecutionsClient()
workflows_client = workflows_v1.WorkflowsClient()

# Construct the fully qualified location path.
parent = workflows_client.workflow_path(project_id, location, workflow_id)

# Execute the workflow adding an dictionary of arguments.
# Find more information about the Execution object here:
# https://cloud.google.com/python/docs/reference/workflows/latest/google.cloud.workflows.executions_v1.types.Execution
execution = executions_v1.Execution(
    name=parent,
    argument='{"searchTerm": "Cloud"}',
)

response = execution_client.create_execution(
    parent=parent,
    execution=execution,
)
print(f"Created execution: {response.name}")

# Wait for execution to finish, then print results.
execution_finished = False
backoff_delay = 1  # Start wait with delay of 1 second.
print("Poll for result...")

# Keep polling the state until the execution finishes,
# using exponential backoff.
while not execution_finished:
    execution = execution_client.get_execution(
        request={"name": response.name}
    )
    execution_finished = execution.state != executions.Execution.State.ACTIVE

    # If we haven't seen the result yet, keep waiting.
    if not execution_finished:
        print("- Waiting for results...")
        time.sleep(backoff_delay)
        # Double the delay to provide exponential backoff.
        backoff_delay *= 2
    else:
        print(f"Execution finished with state: {execution.state.name}")
        print(f"Execution results: {execution.result}")

런타임 인수 전달에 대한 자세한 내용은 실행 요청에서 런타임 인수 전달을 참조하세요.

삭제

이 페이지에서 사용한 리소스 비용이 Google Cloud 계정에 청구되지 않도록 하려면 리소스가 포함된 Google Cloud 프로젝트를 삭제합니다.

  1. 만든 워크플로를 삭제합니다.

    gcloud workflows delete myFirstWorkflow
    
  2. 계속 진행할지 묻는 메시지가 표시되면 y를 입력합니다.

워크플로가 삭제됩니다.

다음 단계