Which of these is true about Spark RDDs?
RDDs will only be executed once a transformation is applied to it
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Data cannot be processed in parallel in RDDs
The dataset can be partitioned across multiple nodes for processing and storage
In case of data failure, data cannot be recreated from a known state and the process has
to start all over again
to start all over again