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Answer: Create additional read replicas, and partition your analytics users to use different read replicas., Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.
To improve report performance and reduce replication lag without altering current reports, two effective approaches are: B. Creating additional read replicas and partitioning analytics users to use different read replicas, which distributes the load and can reduce lag by not overloading a single replica. E. Moving analytics workloads to BigQuery with a streaming pipeline for data updates leverages BigQuery's analytics capabilities and ensures near-real-time data availability without impacting the primary database or read replicas. Option A might improve query performance on the replica but doesn't address replication lag. Options C and D involve risky operations that could disrupt replication without guaranteed performance improvements.
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How can you enhance report performance and reduce replication lag for your Cloud SQL for MySQL read replica, which handles analytics workloads, without modifying existing reports? Select two solutions.
A
Create secondary indexes on the replica.
B
Create additional read replicas, and partition your analytics users to use different read replicas.
C
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.
D
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.
E
Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.