Which of the following function in Spark SQL separates the array's elements into multiple rows with positions and utilizes the column names 'pos' for position and 'col' for elements of the array?

The correct answer is B. posexplode(). The correct answer is B: posexplode(). In Apache Spark SQL, the explode() function (option A) takes an array column and generates one row per element, but it only produces the element values - it does not include positional information. The posexplode() function extends this by…

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Question

Which of the following function in Spark SQL separates the array’s elements into multiple rows with positions and utilizes the column names 'pos' for position and 'col' for elements of the array?

Options

Aexplode()
Bposexplode()
Cpreexplode()
DSeparate()

How the community answered

(31 responses)

A
3% (1)
B
90% (28)
C
6% (2)

Explanation

The correct answer is B: posexplode(). In Apache Spark SQL, the explode() function (option A) takes an array column and generates one row per element, but it only produces the element values - it does not include positional information. The posexplode() function extends this by generating two columns: 'pos' (the zero-based integer position of the element in the array) and 'col' (the element value itself). This makes it useful when the index/position of each array element is needed alongside its value. Option C ('preexplode') does not exist in Spark SQL. Option D ('Separate') is not a Spark SQL function. Therefore, posexplode() is the correct function that matches the described behavior of producing both position ('pos') and value ('col') columns.

Topics

#Spark SQL#Array functions#Data transformation#posexplode

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