Amazon S3
Getting Started with S3 Source Configuration
Requirements:
Active AWS account with S3 access.
Appropriate IAM permissions to access the desired S3 buckets.
Choose the DataBrain Workspace to which you wish to connect the data.
Setup Guide:
Ensure Bucket Accessibility:
Make sure your S3 bucket is active and accessible from DataBrain.
This depends on your AWS account settings and bucket permissions.
Grant Necessary Permissions:
Read Access on Buckets and Objects: Grant read access permissions to the S3 buckets and objects you want to sync.
Fill Up Connection Info:
Provide the following information to connect to your S3 bucket:
Destination Name: A custom name to identify this connection in DataBrain.
S3 Region: The AWS region where your S3 bucket is located (e.g., us-east-1).
S3 Access Key ID: Your AWS Access Key ID for authentication.
S3 Secret Access Key: Your AWS Secret Access Key associated with the Access Key ID.
S3 Bucket Dataset Folder Path: The specific folder path within your bucket (e.g., awss3_folder_test_less/).
S3 Bucket Name: The name of your S3 bucket (e.g., databrain-s3-test-csv).
Table Level: Select whether to interpret data at the Folder or File level.
Permissions:
Permission to list bucket contents.
Permission to read objects from the specified bucket.
If using KMS encryption, permission to use the KMS key for decryption.
Locating the Configuration Details in AWS S3
Destination Name:
Choose a descriptive name for this connection within DataBrain.
S3 Region:
Log in to the AWS Management Console and open the S3 service.
Select your bucket, and find the region information in the bucket's "Properties" tab.
S3 Access Key ID & Secret Access Key:
Generated in the IAM (Identity and Access Management) section of AWS.
Navigate to IAM, select the desired user, go to the "Security credentials" tab, and create or manage access keys.
S3 Bucket Dataset Folder Path:
Navigate to your bucket in the S3 console and note the specific folder path you wish to sync.
S3 Bucket Name:
This is the name of your S3 bucket, visible in the S3 dashboard of the AWS Management Console.
Table Level:
Determine whether your data should be interpreted at the folder level or file level based on your S3 bucket structure and data organization.
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