![]() Your pipeline now automatically creates and updates tables. At the next scheduled AWS Glue crawler run, AWS Glue loads the tables into the AWS Glue Data Catalog for use in your down-stream analytical applications. At the next scheduled interval, the AWS Glue job processes any initial and incremental files and loads them into your data lake. Setting this field to an earlier value triggers AWS Glue to reprocess any files with a larger name.Īt this point, the setup is complete. The AWS Glue job compares this to any new DMS-created incremental files. The file name of the last incremental file. ![]() Setting this field to an earlier value triggers AWS Glue to reprocess the full load file. The AWS Glue job compares this to the date of the DMS-created full load file. When set to “null,” the AWS Glue job only loads data into one partition. Partitions can be valuable when querying and processing larger tables but may overcomplicate smaller tables. When set, the AWS Glue job uses these fields to partition the output files into multiple subfolders in S3. When set to “null,” the AWS Glue job only processes inserts.Ī comma-separated list of column names. When set, the AWS Glue job uses these fields for processing update and delete transactions. When set to true, it enables this table for loading.Ī comma-separated list of column names. In the DynamoDB console, configure the following fields to control the data load process shown in the following table: Field Data does not propagate to your data lake until you review and update the DynamoDB controller table. Data lake configuration: The settings your stack passes to the AWS Glue job and crawler, such as the S3 data lake location, data lake database name, and run schedule.Īfter you deploy the solution, the AWS CloudFormation template starts the DMS replication task and populates the DynamoDB controller table.The table filter and schema filter allow you to choose which objects the replication task syncs. DMS task configuration: The settings the AWS DMS task needs, such as the replication instance ARN, table filter, schema filter, and the AWS DMS S3 bucket location.DMS source database configuration: The database connection settings that the DMS connection object needs, such as the DB engine, server, port, user, and password.The AWS CloudFormation stack requires that you input parameters to configure the ingestion and transformation pipeline: AWS Glue crawler: Builds and updates the AWS Glue Data Catalog on a schedule.AWS Glue trigger: Schedules the AWS Glue jobs.S3 buckets: Stores raw AWS DMS initial load and update objects, as well as query-optimized data lake objects.AWS DMS replication task: Reads changes from the source database transaction logs for each table and stream that write data into an S3 bucket.The second stack contains objects that you should deploy for each source you bring in to your data lake. AWS DMS replication instance: Runs replication tasks to migrate ongoing changes via AWS DMS.Only attach this role to these services and not to IAM users or groups. This role contains policies with elevated privileges. ![]()
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