Configure Cloud Object Storage (GCS, S3, Azure) for Data Lake

Ilum allows you to link CGV, S3, WASBSet HDFS storages to your clusters. Linking storage allows Ilum to automatically configure all your jobs to use your cloud data lakes seamlessly, eliminating the need for manual Spark parameter configuration.

Supported Storage Providers

Provider	Type	Description
Stockage Google Cloud	CGV	Native integration for GCP projects.
Amazon S3	S3	Standard S3 and S3-compatible storage support.
Stockage Blob Azure	WASBS/ABFS	Integration for Azure data lakes.
HDFS	HDFS	Connect to existing Hadoop Distributed File Systems.

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Stockage Google Cloud (GCS)

Stockage Google Cloud (GCS)

Step 1: Create a GCS Bucket

Manif:

Guide en plein écran

1. Create a Google Cloud Project

   • Open Google Cloud Console et allez à Sélecteur de projet / Manage Resources.
   • Cliquer New Project / Create Project.
   • Enter a Project name, choose Organization et Emplacement.

2. Create a GCS Bucket

   • In the Console, navigate to Stockage dans le cloud → Buckets.
   • Cliquer Créer.
   • Enter a globally unique Bucket name (e.g., my-ilum-bucket) and select your Region.
   note

   Remember the bucket name you created - you will need it when adding this storage to Ilum.

3. Create a Service Account and JSON Key

   • Atteindre IAM & Admin → Service Accounts.
   • Cliquer Create Service Account, fill in details, and grant Storage Admin roles.
   • Click the created email, go to the Keys tab, and Create new key (JSON).
   • Save the downloaded JSON file securely.
   important

   Organization Policy Update: In new organizations, creating service account keys might be disabled by default. Contact your administrator if you cannot create keys.

Step 2: Add GCS to Ilum Cluster

Manif:

Guide en plein écran

1. Navigate to Charges → Clusters → Éditer → Stockage → Add Storage.

2. Configure General Settings:

Parameter	Value Example	Description
Nom	my-gcs-storage	Unique name for this storage config.
Type	CGV	Select GCS provider.
Godet d’étincelles	my-ilum-bucket	Bucket for Spark logs/events.
Compartiment de données	my-ilum-bucket	Bucket for your data.

3. Configure GCS Authorization: Open your JSON key file and copy the values:

Parameter	Source Key	Description
Client Email	client_email	Service account email address.
Private Key	private_key	Full key including -----BEGIN....
Private Key ID	private_key_id	Key ID string.

4. Cliquer Envoyer to save.

Amazon S3

Amazon S3

info

The process for adding S3 storage is nearly identical to GCS. You will need to provide your AWS credentials (Access Key and Secret Key) instead of a JSON key file.

1. Navigate to Charges → Clusters → Éditer → Stockage → Add Storage.
2. Select S3 as the Type.
3. Fill in the required fields:

Parameter	Description
Nom	Unique name for this storage config.
Access Key	Your AWS Access Key ID.
Secret Key	Your AWS Secret Access Key.
Region	AWS Region of your bucket (e.g., États-Unis-Est-1).
Endpoint	(Optional) Custom endpoint for S3-compatible storage (e.g., MinIO).

Stockage Blob Azure

Stockage Blob Azure

info

The process for adding Azure storage is nearly identical to GCS and S3. You will need your Azure Storage Account Name and Access Key.

1. Navigate to Charges → Clusters → Éditer → Stockage → Add Storage.
2. Select Azure (or WASBS) as the Type.
3. Fill in the required fields:

Parameter	Description
Nom	Unique name for this storage config.
Account Name	Your Azure Storage Account name.
Account Key	Your Azure Storage Account Access Key.
Container	Name of the container to use.

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Step 3: Verify Connection

To ensure your storage is correctly configured, run a simple Spark job.

1. Create a Code Service:

   • Atteindre Charges → Services → New Service +.
   • Select Type: Code, Langue: Scala, and your Grappe.

2. Execute Test Code: Paste and run the following Scala code:

   Test Storage Connection

   // Write test data
   val données = Seq(("Alice", 34), ("Bob", 45))
   val Df = étincelle.createDataFrame(données).toDF(« nom », "age")
   
   // Replace with your bucket path (e.g., gs://..., s3a://..., wasbs://...)
   val chemin = "gs://my-ilum-bucket/output/" 
   
   Df.écrire.mode(« écraser »).format("csv").save(chemin)
   
   // Read back data
   étincelle.lire.format("csv").load(chemin).montrer()

3. Check Results: If the job completes and displays the data table, your storage connection is active.

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Common Issues & FAQ

Why do I get a "Permission Denied" error?

Cause: The Service Account or User doesn't have permissions to access the bucket. Solution:

1. Go to your cloud provider's console (e.g., Google Cloud Console).
2. Navigate to the bucket's Autorisations onglet.
3. Grant your service account the Storage Admin ou Storage Object Admin role.

Why does it say "Bucket does not exist"?

Cause: The bucket name in your code doesn't match the actual bucket name, or the region is incorrect. Solution:

1. Verify the bucket exists in your cloud console.
2. Check that the bucket name in your code matches exactly (names are often case-sensitive).

Why do I get "Invalid credentials"?

Cause: The keys (JSON or Access Keys) were not copied correctly. Solution:

1. Re-open your key file.
2. Carefully copy the values again. For GCS, ensure you include the -----DÉBUT DE LA CLÉ PRIVÉE----- et -----FIN DE LA CLÉ PRIVÉE----- lines.
3. Re-save the storage configuration in Ilum.