AWS Glue ETL Process

This guide provides step-by-step instructions for setting up an AWS Glue ETL pipeline using S3 as a data source and destination.

Prerequisites

• An AWS account with permissions for S3, Glue, and IAM.
• Data stored in an S3 bucket for ingestion.
• Basic knowledge of AWS services.

Steps to Set Up AWS Glue

1. Create S3 Buckets

1. Source Bucket: Store raw data for ingestion.
2. Destination Bucket: Store processed data output.

2. Create a Crawler in AWS Glue

1. Navigate to AWS Glue.
2. Click on Create a Crawler.
3. Enter a Crawler Name.
4. Add a Data Source:
   • Select S3.
   • Choose the Source Bucket.
   • Ensure the bucket path ends with /.
   • Click Add.
5. Choose an IAM Role with necessary permissions.
6. Create a new Database and name it.
7. Select the database, review, and click Create.
8. Click Run to start the crawler.

3. Verify Data in Tables

• Once the crawler run is complete, navigate to Tables.
• View the ingested data.

4. Create an ETL Job

1. Navigate to AWS Glue > Jobs.
2. Click Create Job.
3. Select the S3 Node as the data source.
4. Choose Data Catalog Table.
5. Select the Database and Table.

5. Transform Data

1. Add a Transform Node.
2. Modify the Schema as needed.
3. Choose Source S3.
4. Drop unnecessary datasets.
5. Note: Arrays cannot be directly converted to CSV.

6. Set Up Data Destination

1. Select S3 as the target.
2. Choose Transform to CSV.
3. Select the Target Bucket.
4. Assign an IAM Role.
5. Set:
   • Glue Version: 4
   • Number of Workers: 2
   • Job Timeout: 5 minutes
6. Click Run Job.

7. Verify Output Data

• After job completion, navigate to the Destination Bucket.
• Verify the processed data.

Conclusion

This guide outlines the essential steps to set up an AWS Glue ETL pipeline efficiently. For further customization, explore AWS Glue job scripts and transformations as needed.

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For any questions or issues, refer to the AWS documentation or you can seek help from me!.