Menjalankan alur kerja menggunakan Library Klien Cloud

Panduan memulai ini menunjukkan cara menjalankan alur kerja dan melihat hasil eksekusi menggunakan Library Klien Cloud.

Untuk informasi selengkapnya tentang cara menginstal Library Klien Cloud dan menyiapkan lingkungan pengembangan, lihat Ringkasan library klien Alur Kerja.

Anda dapat menyelesaikan langkah-langkah berikut menggunakan Google Cloud CLI di terminal atau Cloud Shell.

Sebelum memulai

Batasan keamanan yang ditentukan oleh organisasi mungkin mencegah Anda menyelesaikan langkah-langkah berikut. Untuk mengetahui informasi pemecahan masalah, lihat Mengembangkan aplikasi di lingkungan Google Cloud yang terbatas.

  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. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

  4. To initialize the gcloud CLI, run the following command:

    gcloud init
  5. 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.

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

  7. Enable the Workflows API:

    gcloud services enable workflows.googleapis.com
  8. 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
  9. Install the Google Cloud CLI.
  10. If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

  11. To initialize the gcloud CLI, run the following command:

    gcloud init
  12. 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.

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

  14. Enable the Workflows API:

    gcloud services enable workflows.googleapis.com
  15. 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
  16. (Opsional) Untuk mengirim log ke Cloud Logging, berikan peran roles/logging.logWriter ke akun layanan.

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

    Untuk mempelajari peran dan izin akun layanan lebih lanjut, lihat Memberikan izin alur kerja untuk mengakses Google Cloud resource.

  17. Jika diperlukan, download dan instal alat pengelolaan kode sumber Git.

Men-deploy alur kerja contoh

Setelah menentukan alur kerja, Anda men-deploy alur kerja tersebut agar tersedia untuk dieksekusi. Langkah deploy juga memvalidasi bahwa file sumber dapat dieksekusi.

Alur kerja berikut mengirim permintaan ke API publik, lalu menampilkan respons API.

  1. Buat file teks dengan nama file myFirstWorkflow.yaml dengan konten berikut:

    # 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. Setelah membuat alur kerja, Anda dapat men-deploy-nya, tetapi jangan jalankan alur kerja:

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

    Ganti CLOUD_REGION dengan lokasi yang didukung untuk alur kerja. Wilayah default yang digunakan dalam contoh kode adalah us-central1.

Mendapatkan kode contoh

Anda dapat meng-clone kode contoh dari GitHub.

  1. Clone repositori aplikasi contoh ke komputer lokal Anda:

    C#

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

    Atau, Anda dapat mendownload contoh dalam file ZIP dan mengekstraknya.

    Go

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

    Atau, Anda dapat mendownload contoh dalam file ZIP dan mengekstraknya.

    Java

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

    Atau, Anda dapat mendownload contoh dalam file ZIP dan mengekstraknya.

    Node.js

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

    Atau, Anda dapat mendownload contoh dalam file ZIP dan mengekstraknya.

    Python

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

    Atau, Anda dapat mendownload contoh dalam file ZIP dan mengekstraknya.

  2. Ubah ke direktori yang berisi kode contoh Workflows:

    C#

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

    Go

    cd golang-samples/workflows/executions/

    Java

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

    Node.js

    cd nodejs-docs-samples/workflows/quickstart/

    Python

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

  3. Lihat kode contoh: Setiap aplikasi contoh melakukan hal berikut:

    1. Menyiapkan Library Klien Cloud untuk Alur Kerja.
    2. Menjalankan alur kerja.
    3. Melakukan polling terhadap eksekusi alur kerja (menggunakan backoff eksponensial) hingga eksekusi dihentikan.
    4. Mencetak hasil eksekusi.

    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}")

Menjalankan kode contoh

Anda dapat menjalankan kode contoh dan menjalankan alur kerja. Menjalankan alur kerja akan menjalankan definisi alur kerja yang di-deploy yang terkait dengan alur kerja.

  1. Untuk menjalankan contoh, instal dependensi terlebih dahulu:

    C#

    dotnet restore

    Go

    go mod download

    Java

    mvn compile

    Node.js

    npm install -D tsx

    Python

    pip3 install -r requirements.txt

  2. Jalankan skrip:

    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 .

    Java

    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

    Ganti kode berikut:

    • PROJECT_ID: Google Cloud nama project Anda
    • CLOUD_REGION: lokasi alur kerja Anda (default: us-central1)
    • WORKFLOW_NAME: nama alur kerja Anda (default: myFirstWorkflow)

    Outputnya mirip dengan hal berikut ini:

    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)"]
    

Meneruskan data dalam permintaan eksekusi

Bergantung pada bahasa library klien, Anda juga dapat meneruskan argumen runtime dalam permintaan eksekusi. Contoh:

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}")

Untuk informasi selengkapnya tentang cara meneruskan argumen runtime, lihat Teruskan argumen runtime dalam permintaan eksekusi.

Pembersihan

Agar tidak menimbulkan biaya pada akun Google Cloud Anda untuk resource yang digunakan di halaman ini, hapus project Google Cloud yang berisi resource tersebut.

  1. Hapus alur kerja yang Anda buat:

    gcloud workflows delete myFirstWorkflow
    
  2. Ketika ditanya apakah Anda ingin melanjutkan, tekan y.

Alur kerja akan dihapus.

Langkah berikutnya