Read the schema of a Spark DataFrame.
sdf_schema(x, expand_nested_cols = FALSE, expand_struct_cols = FALSE)
ml_pipeline, or a
Whether to expand columns containing nested array of structs (which are usually created by tidyr::nest on a Spark data frame)
Whether to expand columns containing structs
list, with each
list element describing the
type of a column.
type column returned gives the string representation of the
underlying Spark type for that column; for example, a vector of numeric
values would be returned with the type
"DoubleType". Please see the
Spark Scala API Documentation
for information on what types are available and exposed by Spark.