Create a Spark dataframe containing all combinations of inputs
sdf_expand_grid
Description
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
Usage
sdf_expand_grid(
sc,
...,
broadcast_vars = NULL,
memory = TRUE,
repartition = NULL,
partition_by = NULL
)Arguments
| Arguments | 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+ |
Examples
sc <- spark_connect(master = "local")
grid_sdf <- sdf_expand_grid(sc, seq(5), rnorm(10), letters)