更新叢集

這個範例會逐步引導使用者使用 Python 用戶端程式庫更新 Cloud Dataproc 叢集。

程式碼範例

Python

在試用這個範例之前，請先按照Python使用用戶端程式庫的 Dataproc 快速入門導覽課程中的設定說明操作。 詳情請參閱 Dataproc Python API 參考說明文件。

如要向 Dataproc 進行驗證，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

from google.cloud import dataproc_v1 as dataproc


def update_cluster(project_id, region, cluster_name, new_num_instances):
    """This sample walks a user through updating a Cloud Dataproc cluster
    using the Python client library.

    Args:
        project_id (str): Project to use for creating resources.
        region (str): Region where the resources should live.
        cluster_name (str): Name to use for creating a cluster.
    """

    # Create a client with the endpoint set to the desired cluster region.
    client = dataproc.ClusterControllerClient(
        client_options={"api_endpoint": f"{region}-dataproc.googleapis.com:443"}
    )

    # Get cluster you wish to update.
    cluster = client.get_cluster(
        project_id=project_id, region=region, cluster_name=cluster_name
    )

    # Update number of clusters
    mask = {"paths": {"config.worker_config.num_instances": str(new_num_instances)}}

    # Update cluster config
    cluster.config.worker_config.num_instances = new_num_instances

    # Update cluster
    operation = client.update_cluster(
        project_id=project_id,
        region=region,
        cluster=cluster,
        cluster_name=cluster_name,
        update_mask=mask,
    )

    # Output a success message.
    updated_cluster = operation.result()
    print(f"Cluster was updated successfully: {updated_cluster.cluster_name}")

後續步驟

如要搜尋及篩選其他 Google Cloud 產品的程式碼範例，請參閱Google Cloud 範例瀏覽器。