Which of the following operations can perform an outer join on two DataFrames?
Which of the following operations can perform an outer join on two DataFrames?
The outer join operation on two DataFrames can be performed using the DataFrame.merge() method. This method allows for various types of joins, including outer joins, by using the 'how' parameter with the value 'outer'. The DataFrame.join() method also allows for outer joins, but DataFrame.merge() is specifically designed for merging DataFrames with options for different join types.
D. result_df = df1.join(df2, on="id", how="outer")
D is correct. There is no exists outerJoin() operation in pyspark.
The correct answer is C - DataFrame.outerJoin(). The outer join operation can be performed by specifying the join type as "outer" when calling the outerJoin() function on a DataFrame. The join() function in Spark only performs an inner join, while the merge() function is not a valid function in Spark SQL. The crossJoin() function performs a Cartesian product between two DataFrames, which is not an outer join.
There is no outerjoin, bro! only dataframe.join(how='outer')
this guy always post wrong answers, sometime gpts as well. ignore his commnmets
Wrong answer, check documentation