Which of the following benefits is provided by the array functions from Spark SQL?

The array functions from Spark SQL are a subset of the collection functions that operate on array

columns1. They provide an ability to work with complex, nested data ingested from JSON files or

other sources2. For example, the explode function can be used to transform an array column into

multiple rows, one for each element in the array3. The array_contains function can be used to check

if a value is present in an array column4. The array_join function can be used to concatenate all

elements of an array column with a delimiter. These functions can be useful for processing JSON data

that may have nested arrays or objects. Reference: 1: Spark SQL, Built-in Functions - Apache

Spark 2: Spark SQL Array Functions Complete List - Spark By Examples 3: Spark SQL Array Functions -

Syntax and Examples - DWgeek.com 4: Spark SQL, Built-in Functions - Apache Spark : Spark SQL,

Built-in Functions - Apache Spark : [Working with Nested Data Using Higher Order Functions in SQL

on Databricks - The Databricks Blog]