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Answer: Perform a point-in-time recovery of your Cloud SQL for MySQL database, selecting a date and time before the data was corrupted.
To minimize data loss in a scenario where a Cloud SQL for MySQL database has suffered massive data corruption due to an application error, the best approach is to perform a point-in-time recovery (PITR). This method allows you to restore the database to a specific point in time before the corruption occurred, leveraging the binary logs that were enabled. Option C is the correct choice because PITR is designed for such scenarios, ensuring minimal data loss by restoring the database to a state just before the corruption. Option A suggests using the last automated backup, which might not include all transactions up to the point of corruption, leading to more data loss. Option B is not practical for minimizing data loss as it involves reloading data from CSV files, which would not include any transactions after the initialization. Option D suggests failing over to the HA instance, but this would not help recover from data corruption as the HA instance would also reflect the corrupted state due to replication.
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How can you minimize data loss in a Cloud SQL for MySQL database with high availability (HA) and binary logging enabled after a critical application update caused significant data corruption?
A
Open the Google Cloud Console, navigate to SQL > Backups, and select the last version of the automated backup before the corruption.
B
Reload the Cloud SQL for MySQL database using the LOAD DATA command to load data from CSV files that were used to initialize the instance.
C
Perform a point-in-time recovery of your Cloud SQL for MySQL database, selecting a date and time before the data was corrupted.
D
Fail over to the Cloud SQL for MySQL HA instance. Use that instance to recover the transactions that occurred before the corruption.
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