Dynamically predict optimal parallel apply algorithms
Abstract:
A method, system, and computer program product to analyze data patterns in source workloads and predict the optimal parallel apply algorithms, where the method may include receiving source workload data and replication environment data, where the source workload data includes at least a stream of changes to a target DBMS. The method may also include analyzing characteristics of the source workload data and the replication environment data. The method may also include inputting, as input variables, the characteristics of the source workload data and the replication environment data into a machine learning algorithm. The method may also include obtaining, from the machine learning algorithm, an optimal parallel apply algorithm from a plurality of parallel apply algorithms. The method may also include applying the optimal parallel apply algorithm to the target database management system.
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