Given one or more R vectors/factors or single-column Spark dataframes, perform an expand.grid operation on all of them and store the result in a Spark dataframe
sdf_expand_grid( sc, ..., broadcast_vars = NULL, memory = TRUE, repartition = NULL, partition_by = NULL )
The associated Spark connection.
Each input variable can be either a R vector/factor or a Spark dataframe. Unnamed inputs will assume the default names of 'Var1', 'Var2', etc in the result, similar to what `expand.grid` does for unnamed inputs.
Indicates which input(s) should be broadcasted to all nodes of the Spark cluster during the join process (default: none).
Boolean; whether the resulting Spark dataframe should be cached into memory (default: TRUE)
Number of partitions the resulting Spark dataframe should have
Vector of column names used for partitioning the resulting Spark dataframe, only supported for Spark 2.0+