This article covers connecting Unstructured to Delta Tables in Amazon S3. For information about connecting Unstructured to Delta Tables in Databricks instead, see Delta Tables in Databricks.
If you’re new to Unstructured, read this note first.Before you can create a destination connector, you must first sign up for Unstructured and get your Unstructured API key. After you sign up, the Unstructured user interface (UI) appears, which you use to get the key. To learn how, watch this 40-second how-to video.After you create the destination connector, add it along with a source connector to a workflow. Then run the worklow as a job. To learn how, try out the hands-on Workflow Endpoint quickstart, go directly to the quickstart notebook, or watch the two 4-minute video tutorials for the Unstructured Python SDK.You can also create destination connectors with the Unstructured user interface (UI). Learn how.If you need help, reach out to the community on Slack, or contact us directly.You are now ready to start creating a destination connector! Keep reading to learn how.
Send processed data from Unstructured to a Delta Table, stored in Amazon S3. The requirements are as follows. The following video shows how to fulfill the minimum set of Amazon S3 requirements to store Delta Tables: The preceding video does not show how to create an AWS account or an S3 bucket. For more information about requirements, see the following:
  • An AWS account. Create an AWS account.
  • An S3 bucket. Create an S3 bucket. Additional approaches are in the following video and in the how-to sections at the end of this page.
  • For authenticated bucket read access, the authenticated AWS IAM user must have at minimum the permissions of s3:ListBucket and s3:GetObject for that bucket. Learn how.
  • For bucket write access, authenticated access to the bucket must be enabled (anonymous access must not be enabled), and the authenticated AWS IAM user must have at minimum the permission of s3:PutObject for that bucket. Learn how.
  • For authenticated access, an AWS access key and secret access key for the authenticated AWS IAM user in the account. Create an AWS access key and secret access key.
  • If the target files are in the root of the bucket, the path to the bucket, formatted as protocol://bucket/ (for example, s3://my-bucket/). If the target files are in a folder, the path to the target folder in the S3 bucket, formatted as protocol://bucket/path/to/folder/ (for example, s3://my-bucket/my-folder/).
  • If the target files are in a folder, make sure the authenticated AWS IAM user has authenticated access to the folder as well. Enable authenticated folder access.

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Add an access policy to an existing bucket

To use the Amazon S3 console to add an access policy that allows all authenticated AWS IAM users in the corresponding AWS account to read and write to an existing S3 bucket, do the following.
Your organization might have stricter bucket policy requirements. Check with your AWS account administrator if you are unsure.
  1. Sign in to the AWS Management Console.
  2. Open the Amazon S3 Console.
  3. Browse to the existing bucket and open it.
  4. Click the Permissions tab.
  5. In the Bucket policy area, click Edit.
  6. In the Policy text area, copy the following JSON-formatted policy. To change the following policy to restrict it to a specific user in the AWS account, change root to that specific username. In this policy, replace the following:
    • Replace <my-account-id> with your AWS account ID.
    • Replace <my-bucket-name> in two places with the name of your bucket.
    {
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "AllowAuthenticatedUsersInAccountReadWrite",
            "Effect": "Allow",
            "Principal": {
                "AWS": "arn:aws:iam::<my-account-id>:root"
            },
            "Action": [
                "s3:GetObject",
                "s3:PutObject",
                "s3:ListBucket",
                "s3:DeleteObject"
            ],
            "Resource": [
                "arn:aws:s3:::<my-bucket-name>",
                "arn:aws:s3:::<my-bucket-name>/*"
            ],
            "Condition": {
                "StringEquals": {
                    "aws:PrincipalType": "IAMUser"
                }
            }
        }
    ]
}
  7. Click Save changes.

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Create a bucket with AWS CloudFormation

To use the AWS CloudFormation console to create an Amazon S3 bucket that allows all authenticated AWS IAM users in the corresponding AWS account to read and write to the bucket, do the following.
Your organization might have stricter bucket policy requirements. Check with your AWS account administrator if you are unsure.
  1. Save the following YAML to a file on your local machine, for example create-s3-bucket.yaml. To change the following bucket policy to restrict it to a specific user in the AWS account, change root to that specific username. 
    AWSTemplateFormatVersion: '2010-09-09'
Description: 'CloudFormation template to create an S3 bucket with specific permissions for account users.'

Parameters:
  BucketName:
    Type: String
    Description: 'Name of the S3 bucket to create'

Resources:
  MyS3Bucket:
    Type: 'AWS::S3::Bucket'
    Properties:
      BucketName: !Ref BucketName
      PublicAccessBlockConfiguration:
        BlockPublicAcls: true
        BlockPublicPolicy: false
        IgnorePublicAcls: true
        RestrictPublicBuckets: true

  BucketPolicy:
    Type: 'AWS::S3::BucketPolicy'
    Properties:
      Bucket: !Ref MyS3Bucket
      PolicyDocument:
        Version: '2012-10-17'
        Statement:
          - Sid: AllowAllAuthenticatedUsersInAccount
            Effect: Allow
            Principal:
              AWS: !Sub 'arn:aws:iam::${AWS::AccountId}:root'
            Action:
              - 's3:GetObject'
              - 's3:PutObject'
              - 's3:ListBucket'
              - 's3:DeleteObject'
            Resource:
              - !Sub 'arn:aws:s3:::${BucketName}'
              - !Sub 'arn:aws:s3:::${BucketName}/*'

Outputs:
  BucketName:
    Description: 'Name of the created S3 bucket'
    Value: !Ref MyS3Bucket
  2. Sign in to the AWS Management Console.
  3. Open the AWS CloudFormation Console.
  4. Click Create stack > With new resources (standard).
  5. On the Create stack page, with Choose an existing template already selected, select Upload a template file.
  6. Click Choose file, and browse to and select the YAML file from your local machine.
  7. Click Next.
  8. Enter a unique Stack name and BucketName.
  9. Click Next two times.
  10. Click Submit.
  11. Wait until the Status changes to CREATE_COMPLETE.
  12. After the bucket is created, you can delete the YAML file, if you want.

​
Create a bucket with the AWS CLI

To use the AWS CLI to create an Amazon S3 bucket that allows all authenticated AWS IAM users in the corresponding AWS account to read and write to the bucket, do the following.
Your organization might have stricter bucket policy requirements. Check with your AWS account administrator if you are unsure.
  1. Install the AWS CLI.
  2. Set up the AWS CLI.
  3. Copy the following script to a file on your local machine, for example a file named create-s3-bucket.sh. To change the following bucket policy to restrict it to a specific user in the AWS account, change root to that specific username. In this script, replace the following:
    • Replace <my-account-id> with your AWS account ID.
    • Replace <my-unique-bucket-name> with the name of your bucket.
    • Replace <us-east-1> with your AWS Region.
    #!/bin/bash

# Set variables for the AWS account ID, Amazon S3 bucket name, and AWS Region.
ACCOUNT_ID="<my-account-id>"
BUCKET_NAME="<my-unique-bucket-name>"
REGION="<us-east-1>"

# Temporary filename for the bucket policy.
# Do not change this variable.
POLICY_FILE="bucket_policy.json"

# Create the bucket.
aws s3api create-bucket --bucket $BUCKET_NAME --region $REGION

# Wait for the bucket to exist.
echo "Waiting for bucket '$BUCKET_NAME' to be fully created..."
aws s3api wait bucket-exists --bucket $BUCKET_NAME

# Check if the wait command was successful.
if [ $? -eq 0 ]; then
    echo "The bucket '$BUCKET_NAME' has been fully created."
else
    echo "Error: Timed out waiting for bucket '$BUCKET_NAME' to be created."
    exit 1
fi

# Remove the "block public policy" bucket access setting.
aws s3api put-public-access-block \
    --bucket $BUCKET_NAME \
    --public-access-block-configuration \
    '{"BlockPublicPolicy": false, "IgnorePublicAcls": false, "BlockPublicAcls": false, "RestrictPublicBuckets": false}'

# Check if the operation was successful.
if [ $? -eq 0 ]; then
    echo "The block public policy access setting was removed from '$BUCKET_NAME'."
else
    echo "Error: Failed to remove the block public policy access setting from '$BUCKET_NAME'."
    exit 1
fi

# Create the bucket policy.
cat << EOF > $POLICY_FILE
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "AllowAuthenticatedUsersInAccountReadWrite",
            "Effect": "Allow",
            "Principal": {
                "AWS": "arn:aws:iam::$ACCOUNT_ID:root"
            },
            "Action": [
                "s3:GetObject",
                "s3:PutObject",
                "s3:ListBucket",
                "s3:DeleteObject"
            ],
            "Resource": [
                "arn:aws:s3:::$BUCKET_NAME",
                "arn:aws:s3:::$BUCKET_NAME/*"
            ],
            "Condition": {
                "StringEquals": {
                    "aws:PrincipalType": "IAMUser"
                }
            }
        }
    ]
}
EOF

# Apply the bucket policy.
aws s3api put-bucket-policy --bucket $BUCKET_NAME --policy file://$POLICY_FILE

# Check if the policy application was successful.
if [ $? -eq 0 ]; then
    echo "The bucket policy was applied to '$BUCKET_NAME'."
else
    echo "Error: Failed to apply the bucket policy to '$BUCKET_NAME'."
    exit 1
fi

# Verify the applied policy.
echo "Verifying the applied policy:"
aws s3api get-bucket-policy --bucket $BUCKET_NAME --query Policy --output text

# Remove the temporary bucket policy file.
rm $POLICY_FILE
  4. Run the script, for example: 
    sh create-s3-bucket.sh
  5. After the bucket is created, you can delete the script file, if you want.
To create a Delta Tables in Amazon S3 destination connector, see the following examples. 
import os

from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateDestinationRequest
from unstructured_client.models.shared import (
    CreateDestinationConnector,
    DestinationConnectorType,
    DeltaTableConnectorConfigInput
)

with UnstructuredClient(api_key_auth=os.getenv("UNSTRUCTURED_API_KEY")) as client:
    response = client.destinations.create_destination(
        request=CreateDestinationRequest(
            create_destination_connector=CreateDestinationConnector(
                name="<name>",
                type=DestinationConnectorType.DELTA_TABLE,
                config=DeltaTableConnectorConfigInput(
                    aws_region="<aws-region>",
                    table_uri="<table-uri>",
                    aws_access_key_id="<aws-access-key-id>",
                    aws_secret_access_key="<aws-secret-access-key>"
                )
            )
        )
    )

    print(response.destination_connector_information)
Replace the preceding placeholders as follows:
  • <name> (required) - A unique name for this connector.
  • <aws-region> (required) - The AWS Region identifier (for example, us-east-1) for the Amazon S3 bucket you want to store the Delta Table in.
  • <table-uri> (required) - The URI of the Amazon S3 bucket you want to store the Delta Table in. This typically takes the format s3://my-bucket/my-folder.
  • <aws-access-key-id> (required) - The AWS access key ID for the AWS IAM principal (such as an IAM user) that has the appropriate access to the S3 bucket.
  • <aws-secret-access-key> (required) - The AWS secret access key for the corresponding AWS access key ID.