sdf_expand_grid: Create a Spark dataframe containing all combinations of...

In sparklyr: R Interface to Apache Spark

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)

sparklyr documentation built on May 29, 2024, 2:58 a.m.