Installazione ed esecuzione di un notebook Jupyter su un cluster Dataproc

Obiettivi

Questo tutorial mostra come installare il componente Jupyter su un nuovo cluster e poi connettersi all'interfaccia utente del blocco note Jupyter in esecuzione sul cluster dal browser locale utilizzando il gateway dei componenti di Dataproc.

Costi

In questo documento, utilizzi i seguenti componenti fatturabili di Google Cloud:

• Dataproc
• Cloud Storage

Per generare una stima dei costi in base all'utilizzo previsto, utilizza il calcolatore prezzi.

Prima di iniziare

Se non l'hai ancora fatto, crea un progetto e un bucket Cloud Storage. Google Cloud

1. Configurazione del progetto

   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.

   Go to project selector

   Make sure 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.

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

   To initialize the gcloud CLI, run the following command:

   gcloud init

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

   Go to project selector

   Make sure 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.

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

   To initialize the gcloud CLI, run the following command:

   gcloud init

   1. Creazione di un bucket Cloud Storage nel tuo progetto per archiviare i blocchi note che crei in questo tutorial.

      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.
      I tuoi notebook verranno archiviati in Cloud Storage in gs://bucket-name/notebooks/jupyter.

Esegui la pulizia

Al termine del tutorial, puoi liberare spazio eliminando le risorse che hai creato in modo che non utilizzino più la quota e non generino addebiti. Le seguenti sezioni descrivono come eliminare o disattivare queste risorse.

Elimina il progetto

Il modo più semplice per eliminare la fatturazione è quello di eliminare il progetto creato per il tutorial.

Per eliminare il progetto:

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.

Elimina il cluster

• Per eliminare il cluster:

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

Elimina il bucket

• Per eliminare il bucket Cloud Storage creato nel passaggio 2 della sezione Prima di iniziare, inclusi i blocchi note archiviati nel bucket:

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

Passaggi successivi

• Consulta la guida rapida di Jupyter/IPython Notebook