Create a Spark dataframe containing all combinations of inputs


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


  broadcast_vars = NULL,
  memory = TRUE,
  repartition = NULL,
  partition_by = NULL


Argument Description
sc 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.
broadcast_vars Indicates which input(s) should be broadcasted to all nodes of the Spark cluster during the join process (default: none).
memory Boolean; whether the resulting Spark dataframe should be cached into memory (default: TRUE)
repartition Number of partitions the resulting Spark dataframe should have
partition_by Vector of column names used for partitioning the resulting Spark dataframe, only supported for Spark 2.0+


sc <- spark_connect(master = "local")
grid_sdf <- sdf_expand_grid(sc, seq(5), rnorm(10), letters)