How to load data from Looker to S3 Glue
Learn how to use Airbyte to synchronize your Looker data into S3 Glue within minutes.
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How to Sync to Manually
Step 1: Export Data from Looker
Begin by exporting the required data from Looker. Use the Looker interface to create the desired report or visualization, ensuring it contains all necessary fields and data points. Once your data is prepared, export it in a CSV or JSON format, which are both compatible with AWS services.
Step 2: Set Up an AWS S3 Bucket
Log into your AWS Management Console and navigate to the S3 service. Create a new S3 bucket, providing a unique name and selecting the appropriate region. Configure the bucket settings, ensuring it allows for object uploads and has the necessary permissions for your use case.
Step 3: Upload Data to S3
With your data exported from Looker, upload the CSV or JSON files to your S3 bucket. Use the AWS Management Console for a manual upload, or automate the process using the AWS CLI or SDKs, making sure the files are stored in the correct directory structure within the bucket.
Step 4: Set Up AWS Glue Crawler
Access AWS Glue from the AWS Management Console and create a new Crawler. Configure the Crawler to point to your S3 bucket, specifying the location of your data files. Set the Crawler to detect the data schema automatically to prepare it for further processing.
Step 5: Run the Glue Crawler
Execute the Glue Crawler to scan the S3 bucket and extract the metadata. This step will create a table in the AWS Glue Data Catalog that represents the structure of your data. Review the Data Catalog to ensure the schema has been correctly inferred and adjust if necessary.
Step 6: Create a Glue ETL Job
In AWS Glue, create a new ETL (Extract, Transform, Load) job. Set the source to the table created by the Crawler in the Data Catalog. Define any transformations needed on the data, such as cleaning or reformatting fields, using the Glue Studio interface or by writing custom scripts in Python or Scala.
Step 7: Run the Glue Job and Verify Data
Execute the Glue ETL job to process the data and store the output in your desired destination, whether it be another S3 bucket, an AWS RDS database, or other storage solutions. Once the job completes, verify the output to ensure data integrity and correctness, making adjustments to the ETL process if needed.