Bind multiple Spark DataFrames by row and column

R/mutation.R

sdf_bind

Description

sdf_bind_rows() and sdf_bind_cols() are implementation of the common pattern of do.call(rbind, sdfs) or do.call(cbind, sdfs) for binding many Spark DataFrames into one.

Usage

sdf_bind_rows(..., id = NULL) 

sdf_bind_cols(...) 

Arguments

Arguments Description
Spark tbls to combine.
Each argument can either be a Spark DataFrame or a list of Spark DataFrames
When row-binding, columns are matched by name, and any missing columns with be filled with NA.
When column-binding, rows are matched by position, so all data frames must have the same number of rows.
id Data frame identifier.
When id is supplied, a new column of identifiers is created to link each row to its original Spark DataFrame. The labels are taken from the named arguments to sdf_bind_rows(). When a list of Spark DataFrames is supplied, the labels are taken from the names of the list. If no names are found a numeric sequence is used instead.

Details

The output of sdf_bind_rows() will contain a column if that column appears in any of the inputs.

Value

sdf_bind_rows() and sdf_bind_cols() return tbl_spark