sdf_expand_grid {sparklyr} | R Documentation |
Create a Spark dataframe containing all combinations of inputs
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
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
## Not run:
sc <- spark_connect(master = "local")
grid_sdf <- sdf_expand_grid(sc, seq(5), rnorm(10), letters)
## End(Not run)