在 Dataproc 叢集上安裝及執行 Jupyter Notebook

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目標

本教學課程說明如何在新的叢集上安裝 Dataproc Jupyter 元件，然後使用 Dataproc 元件閘道，從本機瀏覽器連線至叢集上執行的 Jupyter 筆記本 UI。

注意： 執行本教學課程會產生 Google Cloud 費用，詳情請參閱「Dataproc 計價方式」一文。

費用

在本文件中，您會使用 Google Cloud的下列計費元件：

• Dataproc
• Cloud Storage

如要根據預測用量估算費用，請使用 Pricing Calculator。

初次使用 Google Cloud 的使用者可能符合免費試用資格。

事前準備

請建立 Google Cloud 專案和 Cloud Storage bucket。

1. 設定專案

   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.

   In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

   Verify that billing is enabled for your Google Cloud project.

   Enable the Dataproc, Compute Engine, and Cloud Storage APIs.

   Enable the APIs

   Install the Google Cloud CLI.

   如果您使用外部識別資訊提供者 (IdP)，請先 使用聯合身分登入 gcloud CLI。

   如要初始化 gcloud CLI，請執行下列指令：

   gcloud init

   In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

   Verify that billing is enabled for your Google Cloud project.

   Enable the Dataproc, Compute Engine, and Cloud Storage APIs.

   Enable the APIs

   Install the Google Cloud CLI.

   如果您使用外部識別資訊提供者 (IdP)，請先 使用聯合身分登入 gcloud CLI。

   如要初始化 gcloud CLI，請執行下列指令：

   gcloud init

   1. 在專案中建立 Cloud Storage bucket，儲存您在本教學課程中建立的筆記本。

      1. In the Google Cloud console, go to the Cloud Storage Buckets page.

         Go to Buckets

      2. Click Create.
      3. On the Create a bucket page, enter your bucket information. To go to the next step, click Continue.
         1. In the Get started section, do the following:
            • Enter a globally unique name that meets the bucket naming requirements.
            • To add a bucket label, expand the Labels section (), click Add label, and specify a key and a value for your label.
         2. In the Choose where to store your data section, do the following:
            1. Select a Location type.
            2. Choose a location where your bucket's data is permanently stored from the Location type drop-down menu.
               • If you select the dual-region location type, you can also choose to enable turbo replication by using the relevant checkbox.
            3. To set up cross-bucket replication, select Add cross-bucket replication via Storage Transfer Service and follow these steps:

               Set up cross-bucket replication

               1. In the Bucket menu, select a bucket.

               2. In the Replication settings section, click Configure to configure settings for the replication job.

                  The Configure cross-bucket replication pane appears.

                  • To filter objects to replicate by object name prefix, enter a prefix that you want to include or exclude objects from, then click Add a prefix.
                  • To set a storage class for the replicated objects, select a storage class from the Storage class menu. If you skip this step, the replicated objects will use the destination bucket's storage class by default.
                  • Click Done.
         3. In the Choose how to store your data section, do the following:
            1. Select a default storage class for the bucket or Autoclass for automatic storage class management of your bucket's data.
            2. To enable hierarchical namespace, in the Optimize storage for data-intensive workloads section, select Enable hierarchical namespace on this bucket.
               Note: You cannot enable hierarchical namespace in existing buckets.
         4. In the Choose how to control access to objects section, select whether or not your bucket enforces public access prevention, and select an access control method for your bucket's objects.
            Note: You cannot change the Prevent public access setting if this setting is enforced at an organization policy.
         5. In the Choose how to protect object data section, do the following:
            • Select any of the options under Data protection that you want to set for your bucket.
              • To enable soft delete, click the Soft delete policy (For data recovery) checkbox, and specify the number of days you want to retain objects after deletion.
              • To set Object Versioning, click the Object versioning (For version control) checkbox, and specify the maximum number of versions per object and the number of days after which the noncurrent versions expire.
              • To enable the retention policy on objects and buckets, click the Retention (For compliance) checkbox, and then do the following:
                • To enable Object Retention Lock, click the Enable object retention checkbox.
                • To enable Bucket Lock, click the Set bucket retention policy checkbox, and choose a unit of time and a length of time for your retention period.
            • To choose how your object data will be encrypted, expand the Data encryption section (), and select a Data encryption method.
      4. Click Create.
      筆記本將儲存在 Cloud Storage 的 gs://bucket-name/notebooks/jupyter.

   建立叢集並安裝 Jupyter 元件

   建立叢集並安裝 Jupyter 元件。

   注意： 建立叢集時，請指定您在「事前準備」步驟 2 中建立的值區名稱 (只需指定該值區名稱即可) 做為 Dataproc staging bucket (如需設定暫存值區的操作說明，請參閱「Dataproc 暫存和臨時值區」)。筆記本將儲存在 Cloud Storage 的 gs://bucket-name/notebooks/jupyter 中。

   開啟 Jupyter 和 JupyterLab UI

   在 Google Cloud 控制台中點選Google Cloud 控制台元件閘道連結，開啟在叢集主要節點上執行的 Jupyter 筆記本或 JupyterLab UI。

   Jupyter 執行個體顯示的頂層目錄是虛擬目錄，可讓您查看 Cloud Storage bucket 或本機檔案系統的內容。如要選擇位置，請按一下 Cloud Storage 的「GCS」連結，或叢集主要節點本機檔案系統的「Local Disk」。

   1. 按一下「GCS」連結。Jupyter 筆記本網頁介面會顯示儲存在 Cloud Storage bucket 中的筆記本，包括您在本教學課程中建立的筆記本。

   清除所用資源

   完成教學課程後，您可以清除所建立的資源，這樣資源就不會繼續使用配額，也不會產生費用。下列各節將說明如何刪除或關閉這些資源。

   刪除專案

   如要避免付費，最簡單的方法就是刪除您為了本教學課程所建立的專案。

   如要刪除專案：

   注意：刪除專案會造成以下結果：

   • 專案中的所有內容都會遭到刪除。 如果您使用現有專案來進行本文中的工作，刪除專案將一併刪除其中已完成的所有工作。
   • 自訂的專案 ID 會消失。當您之前建立這個專案時，可能建立了想要在日後使用的自訂專案 ID。如要保留使用該專案 ID 的網址 (例如 appspot.com 網址)，請刪除在該專案中選取的資源，而不是刪除整個專案。

   如果打算探索多種架構、教學課程或快速入門導覽課程，重複使用專案有助於避免超出專案配額限制。

   1. In the Google Cloud console, go to the Manage resources page.

      Go to Manage resources

   2. In the project list, select the project that you want to delete, and then click Delete.
   3. In the dialog, type the project ID, and then click Shut down to delete the project.

   刪除叢集

   • 如要刪除叢集：

     gcloud dataproc clusters delete cluster-name \
         --region=${REGION}
     

   刪除值區

   • 如要刪除您在事前準備步驟 2 中建立的 Cloud Storage bucket，包括儲存在 bucket 中的筆記本，請按照下列步驟操作：

     gcloud storage rm gs://${BUCKET_NAME} --recursive
     

   後續步驟

   • 請參閱 Jupyter/IPython Notebook 快速入門指南