在 Dataproc 叢集上安裝及執行 Jupyter Notebook

目標

本教學課程將說明如何在新叢集中安裝 Dataproc Jupyter 元件，然後使用 Dataproc 元件閘道，從本機瀏覽器連線至在叢集中執行的 Jupyter Notebook UI。

費用

In this document, you use the following billable components of Google Cloud:

• Dataproc
• Cloud Storage

To generate a cost estimate based on your projected usage, use the pricing calculator. New Google Cloud users might be eligible for a free trial.

事前準備

如果您尚未建立，請先建立 Google Cloud 專案和 Cloud Storage 值區。

1. 設定專案

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

      Go to project selector

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

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

      Enable the APIs

   5. Install the Google Cloud CLI.

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

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

      gcloud init

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

      Go to project selector

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

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

       Enable the APIs

   11. Install the Google Cloud CLI.

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

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

       gcloud init

2. 在專案中建立 Cloud Storage 值區，以儲存您在本教學課程中建立的任何筆記本。

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

      Go to Buckets

   2. Click add_box 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 (expand_more), click add_box 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 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.
      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.
      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 (expand_more), and select a Data encryption method.
   4. Click Create.
   筆記本將儲存在 Cloud Storage 的 gs://bucket-name/notebooks/jupyter 下。

清除所用資源

完成教學課程後，您可以清除所建立的資源，這樣資源就不會占用配額並產生費用。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：

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」一節的步驟 2 中建立的 Cloud Storage 值區，包括儲存在該值區中的 Notebook 檔案：

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

後續步驟

• 請參閱 Jupyter/IPython Notebook 快速入門指南