sdf_bind
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.
Usage
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
idis 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 tosdf_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