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As a Microsoft Fabric Analytics Engineer Associate, you are tasked with optimizing the performance of read operations on a Delta table in Azure Databricks. The table currently suffers from performance issues due to the presence of a large number of small files, which is causing excessive overhead during read operations. Your solution must not only address the immediate performance issues but also consider long-term maintainability and cost-effectiveness. Which of the following approaches would you choose to optimize the reads from the Delta table? (Choose one option)
A
Increase the batch size of the read operations to reduce the number of read calls.
B
Use the 'optimize' command with the 'ZORDER BY' clause to reorganize and compact the table files, improving read performance by colocating related data.
C
Implement a custom filtering function within the read operation to skip unnecessary data, thereby reducing the amount of data processed.
D
Manually merge the small files into larger files using an external tool, then update the Delta table metadata to reflect the new file structure.