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When optimizing a Spark job that writes data to Azure SQL Database using JDBC, which strategy is considered the least effective?
A
Employing batchsize parameter in the JDBC URL to batch writes
B
Caching the DataFrame before writing to reduce recomputation
C
Leveraging the broadcast join before writing to minimize shuffling
D
Utilizing the repartition method to reduce the number of connections
