Bind multiple Spark DataFrames by row and column

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.

sdf_bind_rows(..., id = NULL)

sdf_bind_cols(...)

Arguments

...

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.

Value

sdf_bind_rows() and sdf_bind_cols() return tbl_spark

Details

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