Spark creates a Directed Acyclic Graph $($DAG$)$ during the creation of a Resilient Distributed Dataset $($RDD$).$

The DAG is associated with the new RDD$.$

If there is an action, the driver program, which invokes calls the action, evaluates the DAG after Spark completes the action.

The pointer responsible for transforming the RDD returns to the Spark driver program.

Spark utilizes the DAG Scheduler to perform a transformation and updates the DAG accordingly.

Select the sequence that explains RDD transformation and actions.

$1>>2>>3>>4>>5$

$2>>3>>4>>1>>5$

$1>>5>>2>>4>>3$

$1>>3>>4>>5>>2$

Status: $[$object Object$]$

$1$ point

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