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How can you optimize the execution planning and performance of a Spark SQL query that involves multiple subqueries and aggregations?
A
Increase spark.sql.broadcastTimeout to accommodate complex query planning.
B
Force all operations to disk using persist(StorageLevel.DISK_ONLY) to ensure stability.
C
Flatten all subqueries into a single, complex query to reduce the execution plan‘s complexity.
D
Break down the query into smaller, manageable parts, caching intermediate results if reused.
