Answer-first summary for fast verification
Answer: In the Query Detail screen, by interpreting the Physical Plan
To diagnose a performance problem induced by not leveraging predicate push-down, the most effective place to look is in the **Query Detail screen** by interpreting the **Physical Plan**. This plan will show whether filters are being pushed down to the data source, which is crucial for identifying the issue. The other options, while related to performance and data reading, do not directly indicate whether predicate push-down was utilized. Option A suggests looking in the Executor's log file, which is not the standard place for such diagnostics. Option B involves noting the size of data read from the Input column in the Stage's Detail screen, which can indicate excessive data reads but not the cause. Option D mentions the Delta Lake transaction log and column statistics, which are unrelated to predicate push-down diagnostics.
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In which section of the Spark UI can you identify performance issues caused by failing to utilize predicate pushdown?
A
In the Executor’s log file, by grepping for "predicate push-down"
B
In the Stage’s Detail screen, in the Completed Stages table, by noting the size of data read from the Input column
C
In the Query Detail screen, by interpreting the Physical Plan
D
In the Delta Lake transaction log. by noting the column statistics