Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a Delta table named Customer. When you query Customer, you discover that the query is slow to execute. You suspect that maintenance was NOT performed on the table. You need to identify whether maintenance tasks were performed on Customer. Solution: You run the following Spark SQL statement: EXPLAIN TABLE customer Does this meet the goal?

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B. No Commands such as `ANALYZE TABLE <table_name> COMPUTE STATISTICS` or basic `SELECT` statements retrieve current statistical information or data content, respectively. These operations do not expose the history of maintenance tasks like OPTIMIZE or VACUUM that have been executed on the Delta table, as they do not query the transaction log.

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A. Yes To identify past maintenance tasks, a command must interact with the Delta Lake transaction log, which is distinct from commands that generate current statistics or retrieve data.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might h

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