Microsoft Fabric Analytics Engineer Associate DP-600
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As a Microsoft Fabric Analytics Engineer Associate working with Azure Databricks, you are tasked with optimizing the performance of write operations to a Delta table that is experiencing performance degradation due to a high volume of small writes. The solution must ensure data integrity, support time travel operations, and minimize the impact on existing workflows. Considering these requirements, which of the following approaches would be the BEST to optimize the writes to the Delta table? (Choose one option)
A
Increase the batch size of the write operations to reduce the number of transactions, though this may not be feasible if the application logic does not support larger batches.
B
Use the 'overwrite' option to replace the entire table with each write operation, which could significantly improve write performance but at the risk of data loss and without support for incremental updates.
C
Implement a staging area to accumulate and combine small writes into larger batches before writing to the Delta table, thereby reducing the number of write operations and associated overhead while maintaining data integrity and supporting all Delta table features.
D
Disable the transaction log for the Delta table to eliminate the overhead of logging, which would speed up writes but at the cost of losing the ability to track changes and perform time travel operations.