map
(Kotlin-specific) Applies the given function to each group of data. For each unique group, the function will be passed the group key and an iterator that contains all the elements in the group. The function can return an element of arbitrary type which will be returned as a new Dataset.
This function does not support partial aggregation, and as a result requires shuffling all the data in the Dataset. If an application intends to perform an aggregation over each key, it is best to use the reduce function or an org.apache.spark.sql.expressions.Aggregator.
Internally, the implementation will spill to disk if any given group is too large to fit into memory. However, users must take care to avoid materializing the whole iterator for a group (for example, by calling toList) unless they are sure that this is possible given the memory constraints of their cluster.