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A data engineer is developing an ETL process based on Spark SQL.

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A data engineer is developing an ETL process based on Spark SQL. The execution fails. The data engineer checks the Spark Ul and can see the ERRORS as follows:

Which two corrective actions should the data engineer perform to resolve this issue?

Choose 2 answers - (Q) Narrow the filters in order to collect less data in the query

A.

Upsize the worker nodes and activate autoshuffle partitions

B.

Upsize the driver node and deactivate autoshuffle partitions

C.

Cache the dataset in order to boost the query performance

D.

Fix the shuffle partitions to 50 to ensure the allocation

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