Final answer:
The flatten() function reduces a multidimensional array to a single-dimensional array by extracting inner array elements, whereas explode() creates multiple rows from a single row containing an array by providing each element its own row.
Step-by-step explanation:
The flatten() function is commonly used in programming to reduce the depth of an array by a single level, turning a multidimensional array into a single-dimensional one. The elements from the inner arrays are extracted and placed into the main array without the array structure that previously contained them.
On the other hand, the explode() function typically refers to a process where a single record or row that contains an array or list is converted into multiple rows in a dataset, with each element of the array or list taking up its own row, accompanied by the other non-array values from the original record.
To illustrate, if you use flatten() on [[1, 2], [3, 4]], the result would be [1, 2, 3, 4]. If explode() is used on a dataframe with a row like {'ID':1, 'Values':[1, 2]}, it would result in two rows: {'ID':1, 'Values':1} and {'ID':1, 'Values':2}.