Professional-Cloud-Database-Engineer Exam Dumps : Google Cloud Certified - Professional Cloud Database Engineer

Create extracts from your on-premises databases periodically, and push these extracts to Cloud Storage.

Upload the changes into BigQuery, and merge them with existing tables.

Use Cloud Data Fusion and scheduled workflows to extract data from MySQL. Transform this data into the appropriate schema, and load this data into your BigQuery database.

Use Datastream to connect to your on-premises database and create a stream. Have Datastream write to Cloud Storage. Then use Dataflow to process the data into BigQuery.

Use Database Migration Service to replicate data to a Cloud SQL for MySQL instance. Create federated tables in BigQuery on top of the replicated instances to transform and load the data into your BigQuery database.

Open a support ticket in Google Cloud to prevent any maintenance in that MySQL instance during the month of December.

Use Cloud SQL maintenance settings to prevent any maintenance during the month of December.

Create MySQL read replicas in different zones so that, if any downtime occurs, the read replicas will act as the primary instance during the month of December.

Create a MySQL regional instance so that, if any downtime occurs, the standby instance will act as the primary instance during the month of December.

Create secondary indexes on the replica.

Create additional read replicas, and partition your analytics users to use different read replicas.

Disable replication on the read replica, and set the flag for parallel replication on the read replica. Re-enable replication and optimize performance by setting flags on the primary instance.

Disable replication on the primary instance, and set the flag for parallel replication on the primary instance. Re-enable replication and optimize performance by setting flags on the read replica.

Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.