Using an Amazon S3 data source

Use an Amazon S3 data source when your document repository is an S3 bucket.

You must create an index before you create a data source. You provide the index identifier as a parameter to the CreateDataSource operation.

The S3 bucket must be in the same Region as the index and Amazon Kendra must have permission to access the S3 bucket that contains your documents. You provide the Amazon Resource Name (ARN) of a role that has access when you create the data source using the RoleARN parameter.

The following examples demonstrate creating an S3 data source. The examples assume that you have already created an index and an IAM role with permission to read the data from the index. For more information about the IAM role, see IAM roles for Amazon S3 data sources. For more information about creating an index, see Creating an index.

CLI

aws kendra create-data-source \
 --index-id index ID \
 --name example-data-source \
 --type S3 \
 --configuration '{"S3n-Configuration":{"BucketName":"bucket name"}}' 
 --role-arn 'arn:aws:iam::account id:role:/role name

Python

The following snippet of Python code creates an S3 data source. For the complete example, see Getting started (AWS SDK for Python (Boto3)).

    print("Create an S3 data source")

    name = "getting-started-data-source"
    description = "Getting started data source."
    s3_bucket_name = "${bucketName}"
    type = "S3"
    role_arn = "arn:aws:iam::${accountID}:role/${roleName}"

    configuration = {"S3DataSourceConfiguration":
        {
            "BucketName": s3_bucket_name
        }
    }

    data_source_response=kendra.create_data_source(
        Configuration = configuration,
        Name = name,
        Description = description,
        RoleArn = role_arn,
        Type = type,
        IndexId = index_id
    )

It can take some time to create your data source. You can monitor the progress by using the DescribeDataSource operation. When the data source status is ACTIVE the data source is ready to use.

The following examples demonstrate getting the status of a data source.

CLI

aws kendra describe-data-source \
 --index-id index ID \
 --id data source ID

Python

The following snippet of Python code gets information about an S3 data source. For the complete example, see Getting started (AWS SDK for Python (Boto3)).

    print("    Wait for Kendra to create the data source.")

    while True:
        data_source_description = kendra.describe_data_source(
            Id = "data source ID",
            IndexId = "index ID"
        )
        status = data_source_description["Status"]
        print("Creating data source. Status: "+status)
        time.sleep(60)
        if status != "CREATING":
            break

This data source doesn't have a schedule, so it does not run automatically. To index the data source, you call the StartDataSourceSyncJob operation to synchronize the index with the data source.

The following examples demonstrate synchronizing a data source.

CLI

aws kendra start-data-source-sync-job \
 --index-id index ID \
 --id data source ID

Python

The following snippet of Python code synchronizes an S3 data source. For the complete example, see Getting started (AWS SDK for Python (Boto3)).

    print("Synchronize the data source.")

    sync_response = kendra.start_data_source_sync_job(
        Id = "data source ID",
        IndexId = "index ID"
    )