A company is migrating a high-throughput, on-premises Oracle database to an Amazon Aurora PostgreSQL-Compatible Edition DB cluster. The migration strategy requires minimal downtime, and a solutions architect has configured AWS DMS with a Change Data Capture (CDC) replication task. During testing, the source Oracle database experiences extremely high CPU utilization, and the DMS task cannot keep up with the volume of changes. Which of the following solutions should the solutions architect implement to reduce CPU utilization on the source database and improve CDC performance?
- Configure AWS DMS to use the Binary Reader method instead of the default Oracle LogMiner to read the redo and archived log files directly.Cevap
- BEnable supplemental logging on all source Oracle tables and configure the AWS DMS task to use Oracle LogMiner with the useLogminerReader task setting set to true.
- CModify the AWS DMS replication task settings to disable transaction-based replication and switch to statement-level logging on the source Oracle database.
- DPerform a replatforming migration using AWS SCT to continuously extract transaction logs directly to Amazon S3, and load them into Aurora PostgreSQL using pg_restore.
Cevap
Configure AWS DMS to use the Binary Reader method instead of the default Oracle LogMiner to read the redo and archived log files directly.
The correct solution is to configure the AWS DMS task to use the Binary Reader method. When migrating from a high-throughput Oracle database, the default LogMiner method consumes significant CPU resources because it operates within the database engine to reconstruct changes. The Binary Reader method reads the redo and archived logs directly from the database file system or Automatic Storage Management (ASM), which minimizes the resource footprint on the source Oracle database and enhances replication performance.
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AWS DMS replication methods (LogMiner vs. Binary Reader) for Oracle CDC